WO2023016750A1

WO2023016750A1 - Implantable device with substance abuse sensing capabilities

Info

Publication number: WO2023016750A1
Application number: PCT/EP2022/069916
Authority: WO
Inventors: Alan Fryer; Jeffrey A. Von Arx
Original assignee: Biotronik Se & Co. Kg
Priority date: 2021-08-10
Filing date: 2022-07-15
Publication date: 2023-02-16

Abstract

The present application relates to a system, comprising a processing unit for detection and/or indication of substance abuse by a patient, one or more implantable sensors, wherein the processing unit comprises an interface for receiving ECG data from the one or more implantable sensors, and wherein the processing unit is configured for detecting and/or indicating whether a substance abuse has occurred, based at least in part on the ECG data.

Description

Implantable Device with Substance Abuse Sensing Capabilities

The present application relates to methods and devices for detecting and/or indicating substance abuse.

According to the US National Survey on Drug Use and Health of 2018, approximately 63 million Americans had used an illicit drug in the past year and 67.1 million Americans had binge drunk within the past month (five or more drinks in 1 day) (Key Substance Use and Mental Health Indicators in the United States: Results from the 2018 National Survey on Drug Use and Health). Abuse of prescription pain medication is the 2^nd most common form of illicit drug use in the US, with 3.6 % of the population (approx. 11.8 million Americans) misusing pain medications.

Almost all people implanted with a Spinal Cord Stimulators (SCS) have tried and failed to manage pain with medications such as morphine or opioids prior to getting the SCS implant, and almost all continue to take pain medications one year after implantation. In fact, 30% of SCS patients have increased use of pain medication one year after implantation of an SCS system. Such high prevalence of prescription pain medication use puts these patients at particularly high risk of pain medication abuse.

It may therefore be seen desirable to monitor the consumption of drugs by patients to help physicians to detect and manage substance abuse.

Electro-chemical analysis of fluids such as blood, urine, sweat, and tears remain the gold standard for detecting substance abuse with the drawback of the necessity of a laboratory analysis. However, there are also other approaches for sensing drug abuse: Mahmud et al. (Mahmud S. et al. 2018. “Wearables Technology for Drug Abuse Detection: A Survey of Recent Advancement” Smart Health 13, 100062, 10.1016/j.smhl.2018.09.002) highlighted developments of wearables for continuous drug monitoring. One specific example of opioid detection obtainable with physiology-based wearable sensors was shown by Mahmud et. al (Mahmud S. et al. “Automatic Detection of Opioid Intake Using Wearable Biosensor”, Int. Conf. Comput. Netw. Commun., Mar 2018). They report 99% accuracy in detecting opioid use in 30 patients each monitored for a four-month ambulatory period with a wrist worn wearable sensor. Their sensor measured three parameters: electrodermal activity (EDA), skin temperature, and tri-axis acceleration.

Another example, performed in the context of ***e detection by a wearable, was reported by Angarita et. al (Angarita et al. 2015, “A remote wireless sensor network/electrocardiographic approach to discriminating ***e use”, Drug and Alcohol Dependence 146, e209). They used a wearable electrocardiogram (ECG) monitor (a commercially available chest strap) to develop an algorithm to analyze the morphological features of the ECG to detect ***e use. Five experienced ***e users were recruited for the study, and they were monitored during exercise, during ***e use, and after oral methylphenidate use (a stimulant frequently used to treat attention deficit hyperactivity disorder (ADHD) and narcolepsy). The system showed a sensitivity of 0.80 and a specificity of 0.90 for detecting ***e use of 8 mg/70kg.

US 10,874,358 B2 further relates to a method for detecting the need for providing assistance to an individual suspected of overdosing on an opiate. The method includes using a wearable device for continuous or intermittent monitoring of one or more physiological parameters of the individual.

US 2018/0228969 Al relates to an implantable device for reversing an overdose of a substance in a person. The device measures the person's respiratory rate and/or the person's activity state and automatically injects a dose of overdose reversal agent in the person if the person's respiratory rate and/or the person's activity state indicate that the person may have overdosed on the substance. However, from respiratory rate or activity data, no specific conclusion as to a substance abuse may be drawn.

The risk arising from substance abuse (or even overdosing) may be harmful or lethal for the patient and can thus not be underestimated. And the known methods and devices do not always lead to satisfactory results. Moreover, the devices used so far either require laboratory analysis or items the patient must wear, which is not always optimal. Particularly, the patient may simply avoid wearing them, such that an abuse may remain undetected. Therefore, there is a need to improve the detection of substance abuse by patients.

This need may at least in part be met by the aspects described herein.

According to a first aspect of the present invention, a system is proposed which comprises a processing unit for detection and/or indication of substance abuse by a patient and one or more implantable sensors. The processing unit comprises an interface for receiving ECG data from the one or more implantable sensors. The processing unit is configured for detecting and/or indicating whether a substance abuse has occurred, based at least in part on the ECG data.

According to a preferred embodiment of the inventive system, one or more implantable sensors are configured to measure ECG data for substance abuse analysis when the patient is in a resting state.

Moreover, according to an embodiment of the inventive system, the ECG data is either raw data measured by the at least one implantable sensor, or the ECG data relates to an ECG signal which has experienced one or more processing steps.

Preferably, according to an embodiment of the inventive system, the processing unit is configured to detect and/or indicate whether a substance abuse has occurred by comparing the at least one parameter associated with the ECG data with a threshold, wherein the a substance abuse has occurred, if the threshold has been exceeded at least a predetermined number of times. One exemplary aspect of the inventive system is that the system further comprises an external device. The processing unit is part of the external device, and the interface is adapted for communication with the one or more sensors.

According to another exemplary aspect of the present inventive system, the system further comprises an implantable device, wherein the processing unit is part of the implantable device.

Moreover, according to an embodiment of the present system, he the interface is adapted for communication with the one or more sensors.

Preferably, according to an embodiment of the present system, the implantable device is an implantable cardiac monitoring device, an implantable cardiac stimulation device, or a neuro-stimulator.

According to an embodiment of the present system, the implantable cardiac stimulation device is a cardiac pacemaker, a implantable cardioverter-defibrillator, or a cardiac resynchronization therapy device.

According to an embodiment of the present system, the neuro-stimulator is a spinal cord stimulator, deep brain stimulator, vagus nerve stimulator or a renal nerve stimulator.

In one aspect of the present invention, a method for detecting and/or indicating substance abuse by a patient is proposed, the method comprising the steps of:

- acquiring ECG data by one or more implantable sensors;

- detect and/or indicate whether a substance abuse has occurred, based at least in part on the ECG data.

According to an embodiment of the present inventive method, the detection and/or indication is performed by an implantable device that includes the one or more sensors or which is in communication with one or more sensors. Furthermore, according to an embodiment of the present inventive method, the detection and/or indication is performed by an external device which is in communication with the one or more sensors.

According to an embodiment of the present inventive method, the implantable device transmits at least a portion of the acquired ECG data to at least one other device for detecting and/or indicating the likelihood that a substance abuse has occurred.

Furthermore, according to an embodiment of the present inventive method, the implantable device is a neuro-stimulator.

According to an aspect of the present invention, a method is proposed for detecting and/or indicating substance abuse by a patient. The method may comprise the steps of acquiring ECG data by one or more implantable sensors and detecting and/or indicating whether a substance abuse has occurred, based at least in part on the ECG data.

This provides the advantage of allowing for a discreet monitoring of a patient by implantable sensors. In other words, it may be possible to acquire, e.g., ECG data without the requirement of having cables and/or detection electronics being visible to the public which may be interpreted as an indication that a patient is currently under medical surveillance such as e.g. substance abuse. This may in particular be seen as advantageous over wearables known from the prior art, as implantable sensors are not visible to persons in close social contact with the patient such as e.g. colleagues, friends and/or family members, in particular, if the patient does not want these social contacts to be aware of a potential tendency of the patient for substance abuse. The present application provides the further advantage that the one or more implantable sensors may be part of an already implanted sensor such as e.g. a (cardiac) monitoring and/or stimulation device, an SCS system (e.g. if the patient suffers from chronical pain) and/or a pacemaker. Therefore, no additional implantable sensors may be required. What is more, the present application further allows for a constant monitoring of the patient and thus a constant evaluation whether the patient has abused a substance. This may be seen as a significant improvement over the prior art which only allows for a momentaneous (e.g. a snap-shot-like/ temporarily) monitoring whether a substance abuse has occurred, e.g., based on an analysis of body fluids which may only allow for a detection and/or indication of a substance abuse over a certain limited period of time in the past. Even if a wearable is worn for detecting and/or indicating whether a substance abuse has occurred, the wearable is nevertheless dependent on the patient’s compliance to wearing the wearable. It is therefore unlikely to achieve an accurate monitoring of the use of a substance (e.g. a pain-relief medication in case of an SCS device), particularly if the patient is willing to obscure substance abuse. The constant monitoring capability disclosed herein may instead allow for a constant monitoring and/or tracking of court ordered rehab and/or people on criminal probation. The constant monitoring capabilities may further be seen advantageous in certain professions in which regular drug testing is required, such as e.g. commercial pilots, police, medical staff (e.g. in a hospital), members of construction projects, etc. A required regular drug testing duty may thus be replaced by the monitoring capabilities as disclosed herein.

The present application may hence facilitate a constant and discreet monitoring of the current handling of substances and may therefore provide an accurate and early indication (e.g. a warning) that a substance abuse has occurred without having to rely on the compliance of the patient.

The ECG data may relate to a constant monitoring of an ECG signal over time (e.g. continuously sampled with a certain sampling frequency). It may also be possible that the ECG data relates to discrete chunks of an ECG signal. Such chunks may be 10 s, 30 s, 1 min, 1 h, etc. long time series measurements of an ECG signal, e.g. sampled once per minute, once per hour, once per day, etc.

According to an embodiment of the present invention, the ECG data for substance abuse analysis is only taken at rest. Rest can be determined by evaluating an accelerometer input, e.g. by recording the accelerometer activity over a period of time and determine a threshold of low activity, wherein activity below said threshold is associated with a resting state. Additionally or alternatively, rest can be determined via analysis of the baseline heart rate over time, wherein a heart rate below or equal to the baseline heart rate is associated with a resting state. Due to rate related ECG changes, taking the ECG at rest may reduce noise in the analysis.

In any case, the ECG data may relate to raw data (e.g. data which has been retrieved from at least one of the one or more implants without further data processing). Contrarily, it may also be possible that the ECG data relates to an ECG signal which has experienced one or more processing steps (e.g. amplification steps, an electronic filtering (e.g. a bandpass filtering of the raw signal), a pre-determination of the length of the P, Q, R, S and/or T interval of the heartbeat, etc.).

The detection and/or indication whether a substance abuse has occurred, may at least in part be based on a comparison of at least one parameter associated with the acquired ECG data with a threshold. It may be concluded, based thereon, that a substance abuse has occurred, if the threshold has been exceeded at least a predetermined number (e.g. one, two, etc.) of times (e.g. absolutely or e.g. in a certain predefined time interval (such as e.g. in 10 s, 1 min, 1 h, etc.)).

It may be possible that the detection and/or indication whether a substance abuse has occurred is solely based on the acquired ECG data. However, it may also be possible that the determination is based at least in part on further data (e.g. from an accelerometer that may also be implanted and/or be part of the same implant that includes the one or more sensors).

A substance may be understood as any kind of drugs (in particular drugs which are considered as harmful for the health of the patient if used or if used above a certain extent, even if applied in a medical context) such as e.g. pain-relief drugs, narcotics, methamphetamines, opioids, morphine, fentanyl, alcohol, etc.

The detection and/or indication of substance abuse may be performed (at least in part) by an implantable device that includes the one or more sensors (acquiring the ECG data) and/or possibly further one or more sensors. In an embodiment, the implantable device indicates substance abuse by demonstrating that substance abuse is occurring with a certain likelihood. Consequently, the implantable device may initiate a notification to a user, as e.g. a physician or caretaking person that they ought to talk with the patient about drug use. In an embodiment, if the patient has been described pain medication, the implantable device may suggest a change of the treatment modality to the physician.

Alternatively, the implantable device detects that substance abuse occurred based on the sensed patient data. It is understood that the detection of substance abuse can only be performed up to a certain likelihood, based on the sensed patient data.

If the detecting and/or indicating whether a substance abuse has occurred is performed by an implantable device, no transmission to an external electronical device may be required for detecting and/or indicating whether a substance abuse has occurred. This provides the advantage that no devices are visible to the public which may indicate potential health related issues of the patient (as outlined above). Besides that, patient compliance may be ensured as the implantable device is preferably a permanently implanted device. By including the one or more sensors in the implantable device a compact and single implant may be provided which allows for monitoring of at least ECG data. An additional benefit may be seen in that data needs not be transmitted by the implantable device for analysis by another device.

The detecting and/or indicating may, however, also be performed (at least in part) by an implantable device which is in communication with the one or more sensors (acquiring the ECG data) and/or one or more further sensors. In other words, it may be foreseen that the implantable device does not include sensors.

For example, the senor(s) may be placed for optimal signal collection, and the implantable device may be implanted closer to the surface of the patient, e.g. to facilitate communication between the implantable device and external devices. Also, the implantable device may relate to an already implanted (cardiac) monitoring and/or stimulation device. In such a case, it may also be possible that the one or more sensors are distributed in the human body (e.g. in a heart area, a spinal area, etc.). The communication between the sensor(s) and the implantable device may be performed based on a wired communication and/or a wireless communication. Such a distributed arrangement of the one or more sensors may provide the advantage that data, which may be associated with the detection and/or indication that a substance abuse has occurred, may be retrieved at various locations of the patient’s body. This may enable statistical support for the detection and/or indication whether a substance abuse has occurred which may thus facilitate a more accurate diagnostic. By using a wireless communication between the one or more sensors and the implantable device, any undesired wiring of the sensors in the human body may be avoided.

The detection and/or indication may also be performed (at least in part) by an external device which is in communication with the one or more sensors.

It may be foreseen that the one or more implantable sensors communicate acquired ECG data (and possibly further (sensor) data) to an external device for further processing. An external device may be a smartphone, tablet, or any other smart device. However, it may also be possible that the external device is a dedicated communication device for communicating with the one or more sensors. Such an external device may e.g. be a hospital device wherein any received data may be stored in a hospital information system and which may be used for detecting and/or indicating whether a substance abuse has likely occurred. It is also possible that the external device may be provided, e.g. as part of a server-based system (e.g. a remote monitoring system) that communicates with the one or more sensors via a relay, e.g. in the form of a smartphone, tablet, or also a dedicated device. The communication of the acquired ECG data to the external device (or an optional external relay) may preferably be a wireless communication.

It may also be possible that the acquired data of the one or more implantable sensors is communicated to an internal device (e.g. an implant) and additionally to the external device for detecting and/ or indicating whether a substance abuse has likely occurred. This may provide additional support and reliability for the detection and/or indication whether a substance abuse has occurred. Transmitting acquired ECG data to an external device (if e.g. implemented as a smartphone) may facilitate the transmission of a warning message to a doctor and/or a relative of the patient that substance abuse has likely occurred, and/or it may reduce the processing requirements of implantable devices which may be limited by a battery.

It may further be possible that the substance abuse is detected and /or indicated before an overdose occurs.

A substance abuse may be understood as a self-administered medication by a patient which has not been verified by an authorized doctor. Such a self-administered medication may be understood as exceeding a certain prescription of a medication administered by a doctor (at least once) or using a substance that has not been prescribed at all. In an example, a doctor may prescribe a certain dose of a pain-relief drug to a patient. However, in some cases, the patient may get used to the prescribed dose of the pain-relief drug (e.g. due to a chronic addiction) and may decide without further consultation with a doctor to increase, e.g. at least double, the dose to feel more comfortable. If done regularly, harmful or even lethal effects for the health of the patient may be a potential result.

However, an overdose may be understood as exceeding (at least once) a certain dose of a drug which may lead to an immediate life threat for the patient. An overdose may (even if an associated threshold is only exceeded once) lead to unconsciousness or even to the death of the patient, at least if not detected and/or indicated early enough such that e.g. an antagonist can be administered.

Detecting and/or indicating substance abuse before an overdose occurs may thus be understood as a precaution to avoid an overdose and to provide respective help (e.g. a psychological consultation and/or an antagonist) to the patient early. In other words, the detection and/or indication may need occur sufficiently frequent and to a sufficient degree of sensitivity to detect and/or indicate substance abuse before an overdose occurs (at which time it may be too late to save the patient from serious harm), e.g. before a patient stops breathing and/or becomes unconscious.

Another aspect of the present application relates to a processing unit for detecting and/or indicating substance abuse by a patient. The processing unit may comprise an interface for receiving ECG data from one or more implantable sensors. The processing unit may be configured to detecting and/or indicating whether a substance abuse has occurred, based at least in part on the ECG data.

The interface may relate to hardware (e.g. one or more antennas, transmission circuitry, etc.) and/or software (e.g. transmission and/or encryption protocols, etc.) related aspects for receiving ECG data from the one or more implantable sensors.

In an example, the processing unit may be configured as an external unit, wherein the interface may be adapted for (wireless) communication with the one or more sensors. In such a case it may be possible that the one or more sensors are implanted (e.g. distributed in the body of the patient). By means of said implementation it may be facilitated that the processing unit may be implemented by a common external device (e.g. smart device, e.g. as outlined above) and/or a hospital system, etc. The wireless communication may be via, e.g. Bluetooth (Low Energy), near field communication (NFC), WiFi, etc.

Another aspect of the present application relates to an implantable device comprising a processing unit as mentioned above. In such an implementation, the processing unit may hence be implanted. This provides the advantage that the detection whether a substance abuse has likely occurred may entirely be done by the implanted device without the requirement for any further external communication entities.

The implantable device may further include the one or more sensors. By including the one or more sensors in the implantable device, a (single) compact device for detecting and/or indicating whether a substance abuse has occurred may be facilitated. The processing unit may receive the ECG data from the one or more sensors, e.g. in a wired manner.

Also in the implementation in an implantable device, the interface may further be adapted for (wireless) communication with the one or more sensors. In such an implementation, the implantable device may not comprise all of the one or more implantable sensors (for acquiring ECG data and possibly for acquiring further data). The communication between the one or more sensors and the processing unit may be based on a wired connection between the one or more sensors and the processing unit or may at least in part be performed wirelessly, e.g. via Bluetooth (Low Energy), near field communication (NFC), WiFi, and/or any type of intrabody communication.

For example, apart from ECG data and sensor(s), at least one of the following sensors may be provided and its data used for the step of detecting and/ or indicating: activity data (e.g. acquired by a movement sensor/an accelerometer (one axis or multiple axes)), a heart rate (e.g. measured by a simple heart rate sensor), a heart rate variability (e.g. measured by a simple heart rate variability sensor), breathing data (e.g. including a breathing rate (e.g. measured by a breathing rate sensor), a breathing rate variability (e.g. measured by a breathing rate variability sensor), a minute ventilation (MV) (e.g. measured by an MV sensor), a MV variability (e.g. measured by an MV variability sensor), a tidal volume (TV) (e.g. measured by a TV sensor), and a TV variability (e.g. measured by a TV variability sensor), temperature data (e.g. measured by a temperature sensor, e.g., including a device pocket temperature sensor), sleep data (including sleep duration data (e.g. measured with a sleep duration sensor) and sleep quality data (e.g. measured with a suitable sleep quality sensor)), a blood pressure (e.g. measured with a blood pressure sensor, e.g., including pulmonary arterial blood pressure data which may be measured with a pulmonary arterial blood pressure sensor), and chemical data (e.g. measured with chemical sensors which may include electrochemical and optochemical data acquired with electrochemical and/or optochemical sensors).

Another aspect of the present application relates to an implantable neuro-stimulator. The implantable neuro-stimulator may comprise: a sensor for acquiring ECG data.

The neuro-stimulator may comprise one or more electrodes (e.g., the neuro-stimulator may comprise two leads, and one or more electrodes per lead) for neuro-stimulation. Said electrodes may at least in part be used for acquiring/ sensing ECG data.

The sensor may be understood to comprise one or more of said electrodes (e.g. a physical (implanted) electrical contact for sensing the voltage associated with an ECG). It may be foreseen to acquire the ECG signal based at least in part on one or more of the electrodes of the neuro-stimulator. The electrodes used for acquiring ECG data may exclusively be used for acquiring ECG data or may at least in part also be used for neuro-stimulation (e.g. in the context of pain-relief). In the latter case, one or more electrodes may be assigned for sensing an ECG for a certain period of time, whereas the same one or more electrodes may be assigned for neurostimulation for another (disjoint) period of time.

The sensor of the implantable neurostimulator or, more generally the one or more implantable sensors as described herein, may sense the ECG data in a near-field manner, i.e. in proximity to the heart. However, they may also be adapted to sense the ECG data in a far- field manner, i.e. at positions farther away from the heart. In any case, it may be required that at least two electrodes are used for sensing an ECG signal. For far-field sensing, the at least two electrodes may be required to be a certain distance apart from each other (e.g. at least 2 cm, 5 cm, 10 cm, or at least 20 cm). It may also be possible that one of the electrodes used for sensing an ECG signal may be implemented by a (metal) housing of the sensor and/or an implantable device such as a neurostimulator comprising the sensor. This may provide the advantage that less electrodes are required for sensing an ECG signal. For example, one or more electrodes may be arranged in an epidural space of the patient. In case more than two electrodes are provided, the selection of the electrodes used for sensing ECG data may be based at least in part on a signal -to-noise ratio derivable from signals of the electrodes.

By using predetermined pairs of said electrodes of the sensor, it may be facilitated to measure different vectors associated with the ECG data. A vector may be understood as a direction of current flow (the current associated with electrodynamics of the heart of the patient) in a certain direction (e.g. from the heart to the left bottom-most area of the feet of the patient). Any other suitable vector may be chosen, wherein each of the vectors may carry one or more indications for certain heart-related issues.

Coming back to the example of a neuro-stimulator, the neuro-stimulator may further comprise a processing unit for detecting and/or indicating whether a substance abuse has occurred based at least in part on the ECG data. The processing unit may be similar to that described above. Additionally or alternatively, the neuro-stimulator may comprise an interface to transmit ECG data to another implant and/or to an external device.

The implantable neuro-stimulator may be implemented as an SCS system. Particularly, if implemented as an SCS system, the substance abuse targeted may be pain medication abuse (e.g. generally opioid and/or morphine). SCS patients may particularly be vulnerable to pain medication abuse because the vast majority of patients may be prescribed high doses of pain medication prior to getting the SCS system (implanted). It is known that the vast majority of patients continues to take pain medications after getting the SCS system (cf. Sharan A., et al., “ Association of Opioid Usage with Spinal Cord Stimulation Outcomes". Pain Medicine 2018; 19: 699-707), which may thus be monitored and managed by the aspects described herein.

Another aspect of the present application relates to a method, performed by an implantable neuro-stimulator. The method may comprise the step of acquiring ECG data.

This implementation in the form of an implantable neuro-stimulator provides the advantage of using an (already) implanted neuro-stimulator (e.g. an SCS device in case of patients suffering from chronical pain) for additionally acquiring ECG data. It may thus be facilitated, by means of the implantable neuro-stimulator, to also acquire data associated with the heartbeat of the patient (without the requirement for further implants). Such an ECG may be understood as a far-field ECG as it is recorded in an area “far-away” from the heart of the patient (which may be seen as the commonly used region for acquiring an ECG).

The method may further comprise detecting and/or indicating, based at least in part on the acquired ECG data, whether a substance abuse has occurred. Based on the acquired ECG data, it may be facilitated to detecting and/or indicating whether a substance abuse has occurred, e.g., as the acquired ECG data may be associated with changes of the electrodynamics of the heart due to substance abuse (e.g. imprinted onto the one or more acquired vectors). This may be seen as beneficial as a severe percentage of patients with an implanted neurostimulator (e.g. for pain relief) suffer from or are at least endangered to abuse substances as said patients tend to be already high-dose opioid users. Therefore, no additional implants are required for the sensing substance abuse.

The determination may be performed similarly to the method for determining substance abuse by a patient as outlined above.

It may be possible that the detection and/or indication whether a substance abuse has occurred is performed on the implanted neuro- stimulator.

However, it may also be possible that at least a portion of the ECG data is transmitted to at least one other device for the detection and/or indication whether a substance abuse has occurred. Said other device may be at least one other implant (e.g. a pacemaker, an implanted processing unit or relay, etc.) and/or at least one external device (as outlined above). Such an implementation may allow that the processing power requirements (and the associated power consumption) of the implanted neuro-stimulator may be minimized. However, and in contrast to a detection using an external test whether a substance abuse has occurred, a local (i.e. on the implanted neuro-stimulator) detection may provide the advantage that less data communication between the sensor for acquiring the ECG data and the external device is required.

It is noted that aspects described herein with reference to a method may generally also be implemented in a device performing that method, even if not expressly mentioned. On the other hand, aspects described with reference to functionality of a device or apparatus may generally also be implemented as method steps.

Regardless of whether the one or more sensors are part of the implantable device and/or neuro-stimulator, it is understood that the present disclosure also includes systems that comprise an implantable device and/or neuro-stimulator as described herein and one or more implantable sensors as described herein. It is noted that the term “implantable” refers to elements that may not have been but are configured for being implanted into a patient. However, the term “implantable” also includes elements that have already been implanted.

The functions/method steps described herein may generally be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Other examples and implementations are within the scope of the disclosure and appended claims. For example, due to the nature of software, functions described above can be implemented using software executed by a processor, hardware, firmware, hardwiring, or combinations of any of these. Features implementing functions may also be physically located at various positions, including being distributed such that portions of functions are implemented at different physical locations. Also, as used herein, the phrase “based on” shall not be construed as a reference to a closed set of conditions. For example, an exemplary step that is described as “based on condition A” may be based on both a condition A and a condition B without departing from the scope of the present disclosure. In other words, as used herein, the phrase “based on” shall be construed in the same manner as the phrase “based at least in part on.”

Computer-readable media includes both non-transitory computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A non-transitory storage medium may be any available medium that can be accessed by a general purpose or special purpose computer. By way of example, and not limitation, non-transitory computer-readable media may comprise RAM, ROM, electrically erasable programmable read only memory (EEPROM), compact disk (CD) ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to carry or store desired program code means in the form of instructions or data structures and that can be accessed by a general -purpose or special-purpose computer, or a general -purpose or special-purpose processor. Combinations of the above are also included within the scope of computer-readable media. The following figures are provided to support the understanding of the present invention:

Fig. 1 Flowchart of an exemplary embodiment of the present application;

Fig. 2 Illustration of an implanted device according to an embodiment of the present application;

Fig. 3 Illustration of a neuro-stimulator according to an aspect of the present application.

The following detailed description outlines possible exemplary embodiments of the invention.

Fig 1 shows a flowchart of an exemplary embodiment of the present application. The embodiment is implemented as a method 100 which may be suitable for detection and/or indication of substance abuse by a patient. Method 100 may comprise the step of acquiring 110 ECG data by one or more implantable sensors. The ECG data may be implemented as it has been described above.

However, it may be foreseen that not only ECG data is acquired. It may be possible that one or more data sets of the following may be acquired: activity data (e.g. acquired by a movement sensor/an accelerometer (one axis or multiple axes)), a heart rate (acquired via the ECG signal), a heart rate variability (acquired via the ECG signal), breathing data (e.g. including a breathing rate (e.g. measured by a breathing rate sensor), a breathing rate variability (e.g. measured by a breathing rate variability sensor), a minute ventilation (MV) (e.g. measured by an MV sensor), a MV variability (e.g. measured by an MV variability sensor), a tidal volume (TV) (e.g. measured by a TV sensor), and a TV variability (e.g. measured by a TV variability sensor), temperature data (e.g. measured by a temperature sensor, e.g., including a device pocket temperature sensor), sleep data (including sleep duration data (e.g. measured with a sleep duration sensor) and sleep quality data (e.g. measured with a suitable sleep quality sensor)), a blood pressure (e.g. measured with a blood pressure sensor, e.g., including pulmonary arterial blood pressure data which may be measured with a pulmonary arterial blood pressure sensor), and chemical data (e.g. measured with chemical sensors which may include electrochemical and optochemical data acquired with electrochemical and/or optochemical sensors). However, it is noted that these types of data and associated sensors are only mentioned exemplarily and that data associated with any other sensor, not mentioned above, may also be acquired. It may be possible that all of the above-mentioned data is acquired by respective sensors which are implanted (e.g. in a single implantable device and/or distributed across several implantable devices). Additionally or alternatively, it may also be possible that one or more of the sensors are external (e.g. an accelerometer of a wearable and/or a smartphone).

The method may further comprise the step of detecting 120 whether a substance abuse has likely occurred, based at least in part on the ECG data, and optionally based on further sensor data as described herein.

As outlined above, it may be foreseen that the determining 120 is based on a comparison of the ECG data (and, optionally, any additional acquired data, e.g., by non-ECG sensors) with a threshold. It may be possible to derive one or more parameters associated with the ECG data such as, e.g., a heart rate, a heart rate variability, morphological data, premature ventricular contraction (PVC) data, and/or P, Q, R, S, and/or T interval characteristics (e.g. a duration, an amplitude, etc.), etc. It may be possible to use a threshold for the one or more derived parameters. If said threshold is undershot (or overshot), e.g. for a certain predetermined number of times in a predetermined time interval or even just once, it may immediately be possible to detect and/or indicate that a substance abuse has occurred.

It is noted that the acquired data associated with the above-mentioned one or more sensors may preferably be chosen such that the data may be suitable for a correlation with each other to indicate abuse of one or more substances. A correlation in this context may be understood as merging two or more acquired data sets (e.g., acquired or associated with respective sensors) to allow for a detection and/or indication whether a substance abuse has occurred. It may be possible that different substances affect the physiology of the patient differently. As an example, it may be possible that a substance abuse not only causes abnormalities in the ECG data (such as e.g. a different ECG pattern) but that it also causes abnormalities in e.g. the motion of the patient which may be acquirable by a movement sensor (e.g. an accelerometer). It may be then be possible that a larger number of abnormalities associated with substance abuse are derivable from the acquired data. This may facilitate an increased reliability when detecting and/or indicating whether a substance abuse has occurred.

It may be possible that the detection whether a substance abuse has occurred is based on an algorithm. It may additionally or alternatively also be possible that different algorithms are used for determining whether substance abuse has occurred. In such an exemplary implementation, each algorithm may be optimized for a particular class of substances abuse. This may be possible if the substances lead to different signatures in the sensor reading. For example, and with respect to ECG data, opioids may cause decreased heart rate (HR), ST abnormalities, QTc prolongation and tall R- and/or S-waves (Wallner, C. et al., “Electrocardiographic abnormalities in opiate addicts". Addition, 103, 12). Cannabis may increase HR, ST and T wave abnormalities and may causes PVCs (Kochar M. et al, 1973, “Electrocardiographic Effects of Mar ihuana" , JAMA, 225, 25-27). Benzodiazepines (such as Valium and Xanax) may increase HR, lead to QTc prolongation and sometimes atrial fibrillation (Rahman A, et al, 2018, “Changes in ECG among Patients with Drug Induced Poisoning in a Tertiary Care Hospital'. Bangladesh Med Res Counc Bull, 44, 160-167). Alcohol may increase HR, P-wave and QTc prolongation, followed by T-wave abnormalities and QRS complex prolongation (Hitesh R. et al., 2018, “Electrocardiogram Changes with acute Alcohol Intoxication: A Systematic Review", Open Cardiovasc Med J. 12, 1-6). Hence, one or more corresponding threshold values may be used (in combination) to determine abuse of these specific substances, for example.

It may be foreseen, with respect to the detection 120, that the detection is based at least in part on an exemplary algorithm which calculates a substance abuse index. The substance abuse index may e.g. be calculated at least in part by combining the two or more of the acquired data sets which may allow for an increased specificity and/or sensitivity over a single acquired data set.

It may be foreseen that the algorithm used to combine/correlate the acquired data sets uses a weighted sum. In such an implementation it may be foreseen that a weighting factor is assigned to each of the at least two acquired data sets. The weighting factors may be understood as an indicator how relevant the weighted acquired data is for the detection whether a substance abuse has occurred. Based on the weighted acquired data sets it may then be possible to derive an indicator (e.g. a number) which may be used as a basis for the determination whether a substance abuse has occurred. As an example, if the substance abuse index exceeds a predefined threshold, it may be concluded that a substance abuse has likely occurred. In an embodiment, multiple different substance abuse indexes based on different weighting of the acquired data set may be used for detection of like abuse of different substances.

In addition or alternatively, it may also be possible that the detection is based at least in part on using fuzzy logic. In such an implementation, it may be possible to assign certain characteristics of the acquired data (sets) to certain substances which may have been abused. Different substances may (in some cases) lead to the same physiological effects, such that the sole study of physiological effects may not always allow a clear answer whether a substance abuse has occurred (e.g. due to known pre-existing diseases of the patient which may mimic a substance abuse) and which substance may have abused. Since said assignment may not always be clear, it may be improved by implementing a fuzzy logic. The application of fuzzy logic may provide a fuzzy assignment which substance may have been abused most likely. This may e.g. comprise assigning e.g. a probability value for an abuse of a certain substance to an acquired data set (e.g. including ECG data and optionally further data). For example, for a shortened P interval it may be determined that it is most likely associated with an abuse of substances A or B. Further acquired data may then be used to further determine whether abuse of substance A or B has likely occurred.

It may additionally or alternatively be possible that the detection and/or indication of substance abuse is implemented using a neural network. This method may then preferably rely on a trained neuronal network wherein the training may be based on using (pre-acquired) human and/or animal data recorded with a known substance dose level. In an example, it may be possible that data has been acquired from humans and/or animals which consumed a certain (known) dose of a (known) substance, e.g. ECG data and optionally additional data as outlined herein. As mentioned above, the consumption may alter one or more physiological parameters (in dependence on the substance). The physiological parameters (e.g. the ECG data etc.) and the corresponding dose of the specific substance may be used as a training data set for the neuronal network. Based on the trained neuronal network, it may then be facilitated to present one or more acquired data sets (e.g. acquired (ECG) data associated with the human heart and locomotion data) to the neuronal network which may then decide (the trained neuronal network) which substance and which dose has most likely been consumed beforehand to explain the presently observable one or more physiological parameters associated with the one or more acquired data sets.

Fig. 2 shows an exemplary embodiment of an implantable device 200 according to an aspect of the present invention. The implantable device 200 may be implemented to perform any of the above-mentioned methods steps.

Implantable device 200 may comprise a processing unit 210 and one or more sensors 220 which may be implemented as described herein.

It may be foreseen that the one or more algorithms used for detecting and/or indicating whether a substance abuse has occurred are stored and/or are executed in processing unit 210. For this purpose, processing unit 210 may be equipped with a central processing unit (CPU), a microcontroller, transient and/or non-transient memory, and/or cache memory, etc. The processing unit may comprise an interface for receiving ECG data from the one or more sensors 220.

The algorithm for calculating the substance abuse index may be implemented in the implantable device itself (e.g. in processing unit 210). This may comprise the aspect that data (raw data and/or a pre-processed data, e.g. amplified, filtered, etc.) from which one or more parameters may be derived (e.g. an ECG morphology, a respiratory rate, a heart rate, etc.), acquired by one or more of one of the one or more sensors 220 is combined to calculate the substance abuse index (as described above with respect to Fig. 1) in the implantable device 200. Additionally or alternatively, it may also be possible that at least a fraction of the data acquired by the one or more sensors is transmitted to one or more further devices. For that purpose, implantable device 200 may possess a communication interface.

For example, the communication interface may be based on Bluetooth (e.g. Bluetooth Low Energy (BLE)), WiFi, Near Field Communication (NFC), Medical Implant Communication Service (MICS), Intra-Body Communication (IBC), etc. Via the communication interface (ECG and optional further) sensor data and/or warnings and/or notifications etc. may be transmitted to an internal and/or external device as described herein for further processing.

The internal and/or external device may then forward the data to one or more remote servers, e.g. over the internet, e.g. wirelessly (5G, WiFi, etc.) and/or wired (e.g. ethernet, fiber-based, etc.).

The one or more remote servers may be capable of storing the received data and/or may additionally be capable of executing an algorithm involving the received data to detect and/or indicate whether a substance abuse has occurred. Said detection and/or indication may be based on calculating the substance abuse index (which may be stored in addition to the received data). The one or more remote servers may e.g. be capable of transmitting the calculated substance abuse index to entitled doctors and/or any other entitled third persons/parties.

The advantage of calculating the substance abuse index on a remote server may be seen in minimizing the computation which is to be done in the implantable device (which may have limited memory, limited processing capability, limited energy). Moreover, calculating the substance abuse index on one or more remote servers may allow more sophisticated (e.g. faster, resource intensive, more reliable, etc.) algorithms to be used for the calculation.

The communication interface may also be configured to receive one or more programming commands from an internal and/or external device. The one or more programming commands may e.g. relate to a reconfiguration of the program being executed on the implantable device (e.g. a stimulation mode for an SCS implant or a stimulation mode of a pacemaker). The programming commands may also refer to new and/or updated algorithms (as described herein) which may be executed on the implantable device. The programming commands may also refer to one or more requests. A request may e.g. comprise a request for a system status (e.g. the current battery power, a current operation mode, etc.).

It may also be possible to use acquired data sets (using one or more of the above-mentioned sensors) to calculate one or more trends (e.g. on the implantable device and/or on one or more remote servers). A trend may be understood as a time evolution of data associated with the one or more sensors. As an example, it may be possible to derive the duration of the QT interval of a heartbeat every hour for one week. Based on said example, it may be possible to derive the time evolution of the duration of the QT interval of the heartbeat over the course of one week.

It may be possible to report the one or more trends for each of the relevant acquired data sets by the one or more sensors to a doctor and/or a relative and/or any other entitled person. The one or more trends which are reported may be reported in addition to the calculation of a substance abuse index (as outlined above) or any other suitable indicator whether a substance abuse has occurred. However, it may also be possible that the one or more trends can be presented in lieu of the index (or any other suitable indicator). The general advantage of showing trends in lieu of an index (or any other suitable indicator) can be seen in the aspect that it is in general more difficult to get regulatory approval to calculate a substance abuse index (or any other suitable indicator) due to the need to show efficacy of an index in a large clinical trial. A trend of sensed parameters can be displayed without any claims of efficacy pertaining to substance abuse detection. Physicians can view the trended data and draw their own conclusions about likelihood of substance abuse based on published papers. This may be an interim solution while a clinical trial on an index algorithm is being run.

For the sake of completeness, it may in general be preferred by doctors to be provided with a single index because it is a single number (or generically any indicator which may be expressed in a single number) representing the combined acquired data sets (e.g. for calculating the index), and may therefore allow an easier interpretation, e.g., the likelihood of a substance abuse having occurred, e.g., based on the aspect whether the value of the index exceeds a predefined threshold which may be interpreted as a substance abuse which has likely occurred. In turn, a trend may allow deeper insights, e.g. a temporal evolution of an abuse.

The one or more sensors 220 may preferably be active implantable sensors (AIMDs). While Fig. 2 shows the one or more sensors 220 as part of the implantable device 200, it is also possible that one or more of sensors 220 is external to implantable device 200, e.g. corresponds to a separate implant or is part of a separate implant.

External sensors (which still preferably are implanted sensors) may be in a wired communication with processing unit 210. Additionally or alternatively, external sensors may be in communication with processing unit 210 via its communication interface, as outlined above, and/or with a separate communication interface of processing unit 210 for sensor communication.

Additionally or alternatively, it may also be possible that the one or more external sensors forward the acquired data (by the one or more sensors) to an external device (e.g. a smartphone and/or any other dedicated device (e.g. a hospital device, an OEM device, etc.)) which may then perform the step of detection and/or indication. The communication between the one or more sensors and the external device may be based on Bluetooth (e.g. Bluetooth Low Energy (BLE)), WiFi, NFC, MICS, etc. It may be foreseen that the one or more sensors are in direct communication with the external device. Additionally or alternatively it may be foreseen that at least a portion of the acquired data, by the one or more sensors, is transmitted to another implantable device first (e.g. based on data hopping, wherein the communication may e.g. be based on MICS, a wired connection among the implantable sensors and the another implantable device, an IBC, etc.) which may then forward the respective data to the external device.

For example, movement sensors can easily be implemented in AIMDs as accelerometers, e.g. multi-axis accelerometers. Breathing rate, breathing rate variability, TV, TV variability, and/or MV sensors can all be sensed in AIMDs by measuring the impedance across appropriately spaced electrodes implanted in the chest. ECG data, from which heart rate, heart rate variability, PVCs, Long QT intervals, etc. may be derived, can be sensed by appropriately placed electrodes in the chest and/or epidural space, for example. A temperature sensor can be implemented in an AIMD by a thermistor, thermocouple, or PN junction diode which may be in thermal contact with a housing of the AIMD. Sleep duration sensors and sleep quality sensors can be implemented by combining an ECG/heart rate sensor, motion sensor(s), and/or breathing sensor(s). The one or more sensors may further relate to implantable blood pressure sensors. It may further be possible that at least some of the sensors are based on electrochemical or optochemical techniques. It is further noted that these sensor implementations are only mentioned exemplarily. It may also be possible that any other suitable sensor may also be implemented.

In an embodiment, implantable device 200 may be implanted as an implantable monitoring device (in such a case, for example, all sensors 220 may be external to the device 200). Incorporating substance abuse detection capability (as described above) into a monitoring device allows doctors to track and to help to manage substance abuse by patients. In such an implementation it may be foreseen that the implantable device continuously evaluates acquired data (acquired by means of one or more sensors) to detect and/or indicate whether a substance abuse has likely occurred (and optionally at which level the substance abuse has likely occurred). The detection and/or indication whether a drug abuse has occurred may be based on the algorithms described above with respect to processing unit 210. Said monitoring may preferably be applied in industries that require regular drug testing, such as members of the medical staff (e.g. health care and hospital workers), commercial pilots, and certain Government workers. Workers may then have a choice to either continue the current practice of regular drug testing (e.g. a drug test once a day, once a week, once a month, once a year, etc.) with body fluid samples, or to have a monitor implanted. For the employee the benefit of the monitor may be seen in an increased convenience over regular body fluid sample collection. The advantage for the employer may be seen in a more continuous monitoring of a potential drug abuse by the employee rather than collecting distinct samples (e.g. once a year) which may not allow a comprehensive conclusion concerning potential drug habits of the employee in between two sample collections. Although the sensitivity and specificity of the combined implanted sensors may be less than the well-established chemical analysis of body fluids, the fact that the monitoring is continuous may still make it more effective at identifying substance abuse issues. Should the device detect potential substance abuse, the result may be followed up with a traditional body fluid analysis to confirm the result. It may further be foreseen that the monitoring device may automatically inform the employer whether a drug abuse has occurred (and optionally about the frequency of a potential drug abuse).

It may further be foreseen that the implantable device 200 (as described beforehand) may be implemented as an implantable drug pump (not shown in Fig. 2). The implantable drug pump may be an intrathecal pain pump which may be configured to directly deliver pain-relief drugs to the spinal cord of the patient. In such drug pumps, the one or more sensors 220 and algorithms (e.g. for detecting and/or indicating whether a substance abuse has occurred, as outlined above with respect to processing unit 210) can be used as feedback (which may optionally be understood as a closed-loop operation) to inhibit drug delivery by the SCS system if a drug use is at a level where it is detectable with the algorithms. In such an implementation, it may be facilitated to ensure that a patient is not overdosed with pain-relief drugs and the drug delivery by the SCS implant may be adjusted to comply with a potential self-medication by the patient (e.g. if the patient consumes an amount of a pain-relief drug which may exceed a prescription by a doctor, the drug delivery by the SCS system may automatically be minimized). This may in particular ensure that disadvantageous effects on the health state of the patient (or even lethal effects) are avoided.

In another exemplary embodiment, the above-mentioned implantable device (as described above with respect to Fig. 2) may be implemented in a drug pump that counteracts a potential overdose. The drug pump may be implanted in patients at high risk of drug overdose. They may be used to potentially detect and treat an overdose. When the drug pump detects high levels of drug use (e.g. a drug dose which may be regarded as hazardous for the health of the patient), the drug pump may initiate an automatic pumping of antidotes into the patient. For example, in the exemplary case of high levels of opioids or heroin, the drug pump may automatically pump in an opioid antagonist such as Naloxone. For that purpose, the implantable drug pump may comprise a reservoir which may contain an antagonist such as e.g. Naloxone. Naloxone may quickly restore normal respiration to a person whose breathing has slowed as a result of overdosing with heroin or prescription opioid pain medications (cf. National Institute on Drug Abuse, https://www.drugabuse.gov/drug-topics/opioids/opioid- overdose-reversal-naloxone-narcan-evzio). Such a decrease of a breathing rate (e.g. a number of breathing cycles per time interval (e.g. 10 breathing cycles per 10s, 10 breathing cycles per min, an apnea, etc.)) of a patient may in this case be detected by one or more breathing sensors. In addition, it may be possible that the drug pump transmits a notification to entitled third parties if an overdose (e.g. accompanied by a Naloxone administering) of a patient has been detected. Such a system may provide the advantage that it may (automatically) save lives. As an example, 71,108 people died of drug overdose in the US in 2019 (Stephenson, J. “Drug Overdose Deaths Head Toward Record Number in 2020, CDC Warns'', https://jamanetwork.com/channels/health-forum/fullarticle/2772241) who may, at least in part, have been rescued by aspects of the present application.

Fig. 3 shows an exemplary illustration of an SCS device 300 with ECG sensing capability. As outlined above, it may be beneficial to use an (already) implanted SCS device for acquiring data (e.g. ECG data) to detect and/or indicate whether a substance abuse has occurred.

The electronics of SCS device 300 may be enclosed in a titanium housing 301.

The SCS device 300 may comprise a header 302 where leads associated with the SCS device may be connected. It may be foreseen that there are, e.g., two leads wherein each of the leads may comprise eight electrodes. Thus, 16 connections may enter the titanium housing 301 at the position of header 302 through hermetic feedthroughs 303 (in other examples, a different number may be used, such as 2, 4, 8, 32, etc.). In addition to the 16 lead electrode connections, there may be one connection 304 to the titanium housing 301 which may also serve as an electrode.

In the following, the actual signal processing steps (e.g. of an acquired ECG signal) are described. Inside the (hermetic) titanium housing 301, acquired signals, fed into the titanium housing 301 by means of connect! on(s) 303, may pass through high voltage protection circuitry 310. This high voltage protection circuitry may clamp high voltages and may protect the electronics of the SCS device against potential (high voltage) defibrillator shocks applied to a patient. The circuity then passes through a multiplexer (MUX) 320. This MUX 320 may select which electrodes are connected for ECG sensing, and which are connected for therapy output, e.g. to output signals to the one or more electrodes used for neurostimulation (e.g. pain-relief). For that purpose, therapy output circuitry 390 may be understood as a signal generator which generates the electrical pulses for neurostimulation. Said generated pulses may e.g. be transmitted to the respective location in an area of the spinal cord by means of the above-mentioned electrodes. It may be possible that therapy output circuitry 390 possesses one or more programs among which a patient may select. Each of the programs may relate to different sequences of stimulation pulses which may lead to different levels of pain-relief. The MUX 320 may be controlled by a control circuitry 370. Control circuitry 370 may be configured to decide which of the electrodes shall be used for neurostimulation and which of the electrodes shall be used for sensing an ECG signal and control MUX 320 accordingly. Control circuitry 370 may e.g. be provided with an algorithm based on which the assignments of the electrodes may be performed.

A differential signal (e.g. between two electrodes) selected by the MUX 320 may then pass through bandpass filters 330 that may filter out signals outside of the ECG frequency range to obtain ECG data and/or an ECG signal. The ECG frequency range of interest may be ~0.3 Hz to -2 kHz (however, also other frequency ranges may be considered). The filtered signal may then be amplified by one or more amplifiers 340. The signal may then be digitized by an analog-to-digital converter (ADC) 350 and may be sent to the ECG signal processing circuitry 360. Signal processing circuitry 360 may comprise a CPU, a memory, a cache, etc. which may be used to execute one or more of the above-mentioned algorithms (described with respect to Fig. 1 and with reference to processing unit 210 of Fig. 2). In other examples, also several differential signals may be selected at the same time.

Also shown in Fig. 3 is a power source 380 (i.e. a battery) for powering the SCS device 300.

SCS devices known from the prior art do not sense ECGs. Most SCS devices used today use their electrodes solely for stimulation (e.g. of the spinal cord for pain-relief) and not for sensing. If presently used SCS devices allow sensing, the sensing may be limited to sensing of an evoked response in the nerves being stimulated, however, not ECGs. However, the electrodes in the exemplary SCS device are configured to be used for sensing an ECG. Since SCS device 300 may have 16 or more electrodes on leads, plus the titanium housing 301 which may also be used as an electrode, more than one vector may be used for ECG sensing, and there are plenty of vectors to choose from for obtaining an ECG.

A preferred sensing vector would be one of the electrodes on the lead in the epidural space, and the titanium housing 301 of the SCS device 300 may be used as the second electrode which is typically located in the lower back of the patient. This may be seen as the preferred vector because it is a long vector, wherein longer vectors may generally be better at picking up farther field signals such as the ECG (the ECG in the context of the present embodiment may be understood as far field because the electrodes used to sense the ECG are relatively far from the heart as compared to the chest electrode positions of conventional, dedicated ECG sensors). For example, a distance between the electrode in the epidural space and the housing 301 may be at least 2 cm, 5 cm, 10 cm, or at least 20 cm.

Two electrodes in the epidural space may also suffice as the sensing vector, particularly if the two electrodes are some distance away from each other. For example, they could be at least 1 cm, at least 2 cm, at least 5 cm, at least 10 cm away from each other. In an example, SCS device 300 may comprise electrodes El to E8. On atypical eight electrode percutaneous SCS lead (the electrodes furthest apart (from each other) i.e. El to E8) may be a better choice than adjacent electrodes El to E2 to sense an ECG. It may also be important to choose electrodes that are not being used for active spinal cord stimulation since the electrode polarization (when used for stimulating) may affect the sensing of an ECG. However, if a stimulating electrode is exemplarily used for ECG sensing, a blanking for the sense function during stimulation bursts may be required to avoid the above-mentioned drawbacks.

In other words, a dedicated electrode(s) may be used for ECG sensing or an electrode(s) may be used for ECG sensing and stimulating at different (disjoint) periods of times.

It may be foreseen that the SCS device 300 automatically chooses electrodes that are not actively being used for spinal cord stimulation such that crosstalk from a stimulating electrode to a sensing electrode may be avoided. When a patient and/or a doctor changes the stimulation electrodes (e.g. if the SCS device 300 is equipped with one or more selectable stimulating programs) the system may automatically update the ECG sensing electrodes to ensure that no stimulation electrode is used for sensing.

It may additionally or alternatively be foreseen that the SCS device 300 automatically chooses the two electrodes (or one electrode and the titanium housing 301) for sensing of an ECG signal that are farthest apart (longest vector) and not currently used as stimulation electrodes.

Additionally or alternatively, it may be foreseen that the SCS device 300 may change vectors automatically if the sensed ECG signal to noise ratio drops below a certain threshold, again choosing electrodes that are currently not used as stimulation electrodes. In this way the SCS device 300 may try to maintain an adequate signal to noise ratio on the sensed ECG signal.

Claims

1. A system, comprising a processing unit (210) for detection and/or indication of substance abuse by a patient, one or more implantable sensors (220), wherein the processing unit comprises an interface for receiving ECG data from the one or more implantable sensors, and wherein the processing unit is configured for detecting and/or indicating whether a substance abuse has occurred, based at least in part on the ECG data.

2. The system according to claim 1, wherein the one or more implantable sensors are configured to measure ECG data for substance abuse analysis when the patient is in a resting state.

3. The system according to one of the claims 1 or 2, wherein the ECG data is either raw data measured by the at least one implantable sensor, or the ECG data relates to an ECG signal which has experienced one or more processing steps.

4. The system according to one of the preceding claims, wherein the processing unit is configured to detect and/or indicate whether a substance abuse has occurred by comparing the at least one parameter associated with the ECG data with a threshold, wherein the a substance abuse has occurred, if the threshold has been exceeded at least a predetermined number of times.

5. The system according to any of the preceding claims, the system further comprising an external device, wherein the processing unit (210) is part of the external device, and wherein the interface is adapted for communication with the one or more sensors.

6. The system according to one of the claims 1 to 4, the system further comprising an implantable device (200), wherein the processing unit (210) is part of the implantable device. The system of claim 6, wherein the interface is adapted for communication with the one or more sensors. The system of one of the claims 6 or 7, wherein the implantable device is an implantable cardiac monitoring device, an implantable cardiac stimulation device, or a neuro-stimulator (300). The system of claim 8, wherein the implantable cardiac stimulation device is a cardiac pacemaker, an implantable cardioverter-defibrillator, or a cardiac resynchronization therapy device. The system of claim 8, wherein the neuro-stimulator is a spinal cord stimulator, deep brain stimulator, vagus nerve stimulator or a renal nerve stimulator. A method (100) for detecting and/or indicating substance abuse by a patient, comprising: acquiring (110) ECG data by one or more implantable sensors; detect and/or indicate (120) whether a substance abuse has occurred, based at least in part on the ECG data. The method of claim 11, wherein the detection and/or indication is performed by an implantable device (200) that includes the one or more sensors (220) or which is in communication with one or more sensors. The method of claim 11, wherein the detection and/or indication is performed by an external device which is in communication with the one or more sensors. The method according to any of the claims 12 or 13, wherein the implantable device transmits at least a portion of the acquired ECG data to at least one other device for detecting and/or indicating the likelihood that a substance abuse has occurred.

15. The method according to any of the claims 12 to 14, wherein the implantable device is a neuro-stimulator (300).