CN105342583A - Intelligent monitoring device with high-precision step counting function for old people - Google Patents
Intelligent monitoring device with high-precision step counting function for old people Download PDFInfo
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
- A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
- A61B5/0024—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system for multiple sensor units attached to the patient, e.g. using a body or personal area network
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/0245—Detecting, measuring or recording pulse rate or heart rate by using sensing means generating electric signals, i.e. ECG signals
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1116—Determining posture transitions
- A61B5/1117—Fall detection
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1118—Determining activity level
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
- A61B5/681—Wristwatch-type devices
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2503/00—Evaluating a particular growth phase or type of persons or animals
- A61B2503/08—Elderly
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Abstract
The invention relates to the technical field of the medical internet of things, in particular to an intelligent monitoring device with a high-precision step counting function for old people. The intelligent monitoring device comprises a wrist instrument and a waist instrument, wherein the wrist instrument comprises a second processor as well as a pulse sensor, a second Bluetooth interface and an LCD (liquid crystal display) which are connected with the second processor; the waist instrument comprises a first processor as well as a step counting sensor, a high-precision step counting unit, a mobile communication transmission unit and a first Bluetooth interface which are connected with the first processor; the second Bluetooth interface is in Bluetooth communication connection with the first Bluetooth interface; the high-precision step counting unit is used for calculating step data sensed by the step counting sensor to obtain a high-precision step counting result; the high-precision step counting result is send to the wrist instrument through the second Bluetooth interface and displayed on the LCD. Therefore, the physiological status of a monitored person can be judged comprehensively through combination of pulse and steps, and the accuracy for judging the physical health condition is improved obviously.
Description
Technical field
The present invention relates to medical technology of Internet of things field, particularly a kind of old people's intelligent monitoring device of high accuracy meter step.
Background technology
According to the 6th national census data, 60 years old and above population account for 13.26% of total population ratio, and wherein 65 years old and above population account for 8.87% of total population ratio.According to current international practice standard, reach 10% when 60 years old and above population account for total population ratio, or over-65s population accounts for total population ratio and reaches 7%, this country is just identified as and enters aging society.It can thus be appreciated that China enters aging society.According to scholarly forecast, will reach about 400,000,000 to the year two thousand fifty China population of more than 60 years old, its proportion accounting for total population will more than 25.2%.When the time comes, just have 1 old people in the middle of every 4 Chinese, China will become the country of height aging.
In order to carry out the relevant spirit of national Internet+Strategic Action Plan, propose according to " Chinese programs for the elderly development " 12 " planning ": " accelerate the construction of family endowment service information system; carry out the pilot work of family endowment information on services platform, and progressively expand pilot scope; Set up programs for the elderly Informatization Cooperative advance mechanism, set up aged information gathering, analytical data platform, perfect elderly people in city and country's weather tracking and monitoring system." we are necessary for the healthy intelligent monitoring device providing real-time high-efficiency of old people.
Because the long-term lives alone of a lot of old man is in, neglected, health status cannot be protected, and cannot be given treatment to timely when meeting accident.On the other hand, in recent years again and again there is the accident that when old man's accidental falls is fallen in a swoon, nobody offers assistance.As can be seen here, problem such as old man's medical treatment daily life etc. highlights.
Along with technology of Internet of things development, the continuous lifting of sensor technology, the appearance of various high-performance sensors, greatly advances the progress of physiological detection technology.Further, the development of embedded technology is also for safeguard and supervision for the aged system provides indispensable technical support.
Now commercially there is many Intelligent bracelet, but the emphasis of numerous Intelligent bracelet is that fresh science and technology is experienced, its major function is motion tracking and the fitness-assisting function of timing, seldom occurs paying close attention to product that is old, the daily physiology monitoring of You Deng colony; Present part Intelligent bracelet on the market has heart rate, pulse detection function, but most Intelligent bracelet is worn in wrist, and it is to the induction of paces data and process accurately, causes accurately judging physiological health situation that is old, You Deng colony.Especially, when paces judge inaccurate, can cause judging that the accuracy of the physiological health situation of old, You Deng colony greatly reduces.
Summary of the invention
Not enough for prior art, the old people's intelligent monitoring device that the object of the present invention is to provide a kind of high accuracy meter to walk, can solve the problem that the health supervision device accuracy of prior art is lower.
Old people's intelligent monitoring device of high accuracy meter step, comprises wrist instrument; Described wrist instrument comprises the second processor and coupled pulse transducer, the second blue tooth interface, LCD display;
Described intelligent monitoring device comprises waist instrument, and described waist instrument comprises first processor and coupled meter walks sensor, high accuracy meter step computing unit, mobile communication delivery unit, the first blue tooth interface;
Described second blue tooth interface is connected with described first blue tooth interface Bluetooth communication;
Described high accuracy meter step computing unit is used for calculating the paces data of meter step sensor institute perception, obtains high accuracy meter step;
Described high accuracy meter step sends to wrist instrument by described second blue tooth interface, shows in described LCD display.
Preferably, described meter step sensor is 3-axis acceleration sensor.
Preferably, the described meter step data to the perception of meter step sensor institute calculates, the meter step data that acquisition high accuracy meter step comprises described meter step sensor obtains carries out combined filter, carries out paces judgement, to being judged to be that effective paces count to the meter step data after combined filter.
Preferably, described combined filter comprises the combination of morphologic filtering computing, medium filtering computing and average filtering operation, and described morphologic filtering computing is for removing baseline drift; Described medium filtering computing is for removing pulse signal and glitch noise, and described average filter computing is used for smooth signal, makes the wave character of signal more obvious.
Preferably, the paces data of described morphologic filtering computing to the perception of meter step sensor institute successively adopt the structural element of two kinds of different lengths to carry out filtering, comprising:
The structural element of g1, carries out filtering by the mean operation of opening and closing and make and break computing, forms first order Morphologic filters, with removing baseline drift, that is:
F1＝(f·g1οg1+fοg1·g1)/2
The structural element of g2, carries out filtering by the mean operation of opening and closing and make and break computing, forms second level Morphologic filters, with removing noise, that is:
F2＝(F1·g2οg2+F1οg2·g2)/2
Wherein, the paces data of f representative meter step sensor institute perception, F1 represents the signal after primary signal first time opening and closing operation, F2 represents the signal after second time opening and closing operation, g1 represents first order morphological structuring elements, g2 represents second level morphological structuring elements, and represent closed operation, ο represents opening operation.
Preferably, described medium filtering computing adopts to be preset the grow up paces data of method to the perception of meter step sensor institute of little sliding window of window and carries out filtering, removes pulse signal and glitch noise, that is:
F3'＝median{f3,N3},f3∈F3
Wherein, median{f3, N3} represent median filtering algorithm, f3 is the value in sliding window, this value derives from transmits the signal F3 that enters, and F3 is one of data F3' after the paces data f of meter step sensor institute perception or morphologic filtering computing, and F3 ' is the signal after medium filtering;
Preferably, described average filter computing adopts the paces data of default moving window size to the signal after medium filtering or the perception of meter step sensor institute to carry out filtering, smoothing to signal;
Wherein, F4 is the signal after the smothing filtering obtained, and m represents the filtering operation that to be averaged from m value of F3 ' signal.
Preferably, describedly paces judgement is carried out to the meter step data after combined filter, to being judged to be that effective paces carry out counting and comprise: if the meter step data after combined filter meets one of following three conditions, be then judged to be effective paces, it is counted:
Fixed threshold condition: the range value of the waveform of data after calculation of filtered, when range value exceedes reservation threshold, judges that this condition meets, and described reservation threshold is repeatedly the empirical value of data test.
F4 (m-1)≤standardvalue and F4 (m) >=standardvalue
Wherein, F4 (m-1) and F4 (m) represents the signal amplitude value in adjacent two moment, the empirical value that standardvalue many data tests obtain; Or
Wave crest and wave trough condition: when a pair adjacent crest and trough being detected, and when the difference of adjacent peaks and trough is greater than a certain standard value, judges that this condition meets; Or
Similarity condition: the similarity of data and standard signal after calculation of filtered, when similarity reaches a certain standard value, judges that this condition meets.
Preferably, describedly paces judgement is carried out to the meter step data after combined filter, to being judged to be that effective paces carry out counting and comprise: if the meter step data after combined filter meets following three conditions simultaneously, be then judged to be effective paces, it is counted:
Fixed threshold condition: the range value of the waveform of data after calculation of filtered, when range value exceedes reservation threshold, judges that this condition meets, and described reservation threshold is repeatedly the empirical value of data test.
F4 (m-1)≤standardvalue and F4 (m) >=standardvalue
Wherein, F4 (m-1) and F4 (m) represents the signal amplitude value in adjacent two moment, the empirical value that standardvalue many data tests obtain; With
Wave crest and wave trough condition: when a pair adjacent crest and trough being detected, and when the difference of adjacent peaks and trough is greater than a certain standard value, judges that this condition meets; With
Similarity condition: the similarity of data and standard signal after calculation of filtered, when similarity reaches a certain standard value, judges that this condition meets.
Preferably, described similarity calculates according to the correlation coefficient of filtered data and standard signal, when correlation coefficient be greater than repeatedly test the empirical value similarvalue obtained time, namely work as R
sfduring >similarvalue, judge that similarity condition meets, wherein
represent the correlation coefficient of filtered data and standard signal, if S
nfor standard signal array, f4
nfor filtered data array, n≤N
p, N
prepresent filtered data array length
The present invention can carry out the physiological situation of comprehensive descision children under guardianship in conjunction with pulse and paces, the accuracy of judgement physiological health situation is significantly improved.
Accompanying drawing explanation
Fig. 1 is old people's intelligent monitoring device preferred embodiment structure chart of high accuracy meter of the present invention step;
Fig. 2 is another preferred embodiment structure chart of old people's intelligent monitoring device of high accuracy meter of the present invention step;
Fig. 3 is another preferred embodiment structure chart of old people's intelligent monitoring device of high accuracy meter of the present invention step.
Detailed description of the invention
Below in conjunction with accompanying drawing, the preferred embodiment of old people's intelligent monitoring device of a kind of high accuracy meter step of the present invention is described in detail.
Fig. 1 is the structural representation of old people's intelligent monitoring device first preferred embodiment of a kind of high accuracy meter step of the present invention, and old people's intelligent monitoring device of high accuracy meter step of the present invention comprises wrist instrument 400;
Pulse transducer 411, second blue tooth interface 403, LCD display 405 that described wrist instrument 400 comprises the second processor 401 and is connected with the second processor 401;
Old people's intelligent monitoring device of high accuracy meter of the present invention step also comprises waist instrument 300, described waist instrument 300 comprise first processor 301 and be connected with first processor 301 meter walks sensor 307, high accuracy meter walks computing unit 309, mobile communication delivery unit 313, first blue tooth interface 303;
Described second blue tooth interface 403 is connected with described first blue tooth interface 303 Bluetooth communication;
Described high accuracy meter step computing unit 309, for calculating the paces data of meter step sensor institute perception, obtains high accuracy meter step;
Described high accuracy meter step sends to wrist instrument 400 by described second blue tooth interface 403, shows in LCD display 405.
Wherein, described high accuracy meter step computing unit 309, for calculating the paces data of meter step sensor 307 perception, obtains high accuracy meter step, in general, the meter step data of this area common methods to 307 perception of meter step sensor can be adopted to calculate, obtain meter step.
Described meter step sensor 307 can adopt the conventional sensor for counting step, preferably, adopts 3-axis acceleration sensor; 3-axis acceleration sensor has the little and lightweight feature of volume, can measurement space acceleration, accurately can reflect the kinetic property of object comprehensively.
Usually, the described meter step data to 307 perception of meter step sensor calculates, obtain high accuracy meter step, comprise: to by meter step sensor 307 obtain count step data carry out conventional filtering, paces judgement is carried out to the filtered meter step data of routine, is judged as effectively counting to judgement paces.
Preferably, the described meter step data to 307 perception of meter step sensor calculates, and obtains high accuracy meter step, comprising: carry out combined filter to the meter step data that meter step sensor 307 obtains, paces judgement is carried out to the meter step data after combined filter, to being judged to be that effective paces count.
Described combined filter comprises the combination of morphologic filtering computing, medium filtering computing and average filtering operation, and described morphologic filtering computing is for removing baseline drift; Described medium filtering computing is for removing pulse signal and glitch noise, and described average filter computing is used for smooth signal, makes the wave character of signal more obvious;
Described morphologic filtering computing, medium filtering computing or average filter computing can adopt this area conventional means to carry out.
Preferably, the paces data of described morphologic filtering computing to the perception of meter step sensor institute successively adopt the structural element of two kinds of different lengths to carry out filtering, comprising:
The structural element of g1, length is N1, carries out filtering by the mean operation of opening and closing and make and break computing, and form first order Morphologic filters, with removing baseline drift, its formula is:
F1＝(f·g1οg1+fοg1·g1)/2(1)
The structural element of g2, length is N2, carries out filtering by the mean operation of opening and closing and make and break computing, and form second level Morphologic filters, with removing noise, its formula is:
F2＝(F1·g2οg2+F1οg2·g2)/2(2)
Wherein, the paces data of f representative meter step sensor institute perception, F1 represents the signal after primary signal first time opening and closing operation, F2 represents the signal after second time opening and closing operation, g1 represents first order morphological structuring elements, g2 represents second level morphological structuring elements, and represent closed operation, ο represents opening operation.
Described medium filtering computing adopts to be preset the grow up paces data of method to the data after morphologic filtering computing or the perception of meter step sensor institute of the little sliding window for N3 of window and carries out filtering, removal pulse signal and glitch noise, sees following formula:
F3'＝median{f3,N3},f3∈F3(3)
Wherein, median{f3, N3} represent median filtering algorithm, f3 is the value in sliding window, this value derives from transmits the signal F3 that enters, and F3 is one of data F3' after the paces data f of meter step sensor institute perception or morphologic filtering computing, and F3 ' is the signal after medium filtering;
Described average filter computing adopts the paces data of default moving window size N4 to the signal after medium filtering or the perception of meter step sensor institute to carry out filtering, smoothing to signal, sees following formula:
Wherein, F4 is the signal after the smothing filtering obtained, and m represents the filtering operation that to be averaged from m value of F3 ' signal.
Describedly paces judgement is carried out to the meter step data after combined filter, to being judged to be that effective paces carry out counting and comprise: if the meter step data after combined filter meets one of following three conditions, be then judged to be effective paces, it is counted:
Fixed threshold condition: the range value of the waveform of data after calculation of filtered, when range value exceedes reservation threshold, judges that this condition meets, and described reservation threshold is repeatedly the empirical value of data test.
F4 (m-1)≤standardvalue and F4 (m) >=standardvalue (5)
Wherein, F4 (m-1) and F4 (m) represents the signal amplitude value in adjacent two moment, the empirical value that standardvalue many data tests obtain
Wave crest and wave trough condition: when a pair adjacent crest and trough being detected, and when the difference of adjacent peaks and trough is greater than a certain standard value, judges that this condition meets.
Particularly, because filtered signal is comparatively level and smooth, therefore use formula (6) (7) (8) to monitor signal, whenever a pair adjacent Wave crest and wave trough being detected, and the difference of Wave crest and wave trough is greater than the empirical value differentvalue of repetitive measurement, then judge to meet Wave crest and wave trough condition.
Crest, trough, crest and trough difference can have various ways, and this area can be adopted to detect Waveform Inspection Technology.
Preferably, following formula can be adopted respectively to detect respectively:
The detection of crest: F4 (m-2)≤F4 (m-1)≤F4 (mH), and F4 (mH) >=F4 (m+1) >=F4 (m+2) (6)
The detection of trough: F4 (m-2) >=F4 (m-1) >=F4 (mL), and F4 (mL)≤F4 (m+1)≤F4 (m+2) (7)
The detection of difference: F4 (mH)-F4 (mL) >=differentvalue (8)
Wherein, F4 (mH) represents current time crest signal amplitude value, F4 (mL) represents current time trough signal amplitude value, F4 (m-1), F4 (m-2), F4 (m+1), F4 (m+2) represent the signal amplitude value in previous moment, front two moment, a rear moment, rear two moment respectively, and differentvalue represents the empirical value of repetitive measurement.
Similarity condition: the similarity of data and standard signal after calculation of filtered, when similarity reaches a certain standard value, judges that this condition meets; Described standard signal builds according to the baseline of filtered data and obtains.
Similarity can be calculated by the variance of filtered data and standard signal, and the difference value between two kinds of signal waveforms that this area can also be adopted to commonly use calculates.
Preferably, when above three conditions all meet, paces judge successfully.
Preferably, described similarity calculates according to the correlation coefficient of filtered data and standard signal, when correlation coefficient be greater than repeatedly test the empirical value similarvalue obtained time, namely work as R
sfduring >similarvalue, judge that this condition meets, wherein
represent the correlation coefficient of filtered data and standard signal, if S
nfor standard signal array, f4
nfor filtered data array, n≤N
p, N
prepresent filtered data array length,
Described mobile communication delivery unit 313 is the delivery module adopting mobile communication technology, can adopt and include but not limited to any one communication technology such as GPRS, GSM, LTE, WIFI.
The present embodiment makes it possible to the physiological status carrying out comprehensive descision children under guardianship in conjunction with pulse and paces, and judgment accuracy is significantly improved.
As another preferred embodiment, as shown in Figure 2, described waist instrument 402 also comprises the heart rate sensor 305, the positioning unit 303 that are connected with first processor 410; Thus make it possible to the physiological status carrying out comprehensive descision children under guardianship in conjunction with heart rate, pulse and paces, judgment accuracy is significantly improved.
Described positioning unit 303 obtains the data such as the current latitude and longitude value of children under guardianship, can adopt any one in GPS module, WIFI locating module, other satellite positioning module.When the physiological status finding children under guardianship is obviously abnormal, the positional information that positioning unit provides can help guardian to find children under guardianship as early as possible, thus give first-aid measures as early as possible, and the physiological status of children under guardianship obviously not abnormal time, guardian also can be helped to understand position or the range of activity of children under guardianship.
Described heart rate sensor 305 gathers and obtains heart rate value and sends to first sensor, simultaneously by the first blue tooth interface and the second blue tooth interface, and 405 shows on the lcd screen.
As another preferred embodiment of the present invention, as shown in Figure 3, the structural representation of old people's intelligent monitoring device second preferred embodiment of a kind of high accuracy meter step of the present invention, also comprise server 520 and the terminal unit 530 of far-end, be connected with the mobile communication delivery unit 313 of waist instrument 301 with wired or wireless mode respectively.
Described server end 520 is responsible for the data receiving the transmission of waist instrument 301, then carry out parsing classification to store, and send real-time monitoring data when there being terminal unit 530 to connect to client 530, server 520 can adopt the distributed or independent any computing equipment arranged, and includes but not limited to the types such as tower, rack, blade type; .
Described terminal unit 530 can show the health of monitored person in real time, ensure that the real-time of monitoring, includes but not limited to that mobile phone, computer, PAD, car-mounted terminal etc. can move or irremovable any equipment.Meanwhile, guardian can also pass through terminal unit 530 access services device, carrys out query history recorded information, ensure that the integrity of monitoring.
Preferably, described terminal unit 530 also with alarm, when monitoring exception for report to the police.
The real-time of the functional realiey of this two part of client and server remote supervision system and continuity, make whole monitoring function more to improve and powerful.
Old people's intelligent monitoring device of high accuracy meter step of the present invention is calculated by the paces data of high accuracy meter step computing unit to the perception of meter step sensor institute, obtains high accuracy meter step;
Further, detect children under guardianship in real time, data front end sensors collected are sent to embedded system and carry out date processing.Server end is sent to again by mobile communication delivery unit 313.Guardian can also read the data on server from terminal unit 530, thus reaches the physical signs such as heart rate, position, cadence of Real-time Obtaining children under guardianship.Old people's intelligent monitoring device that a kind of high accuracy meter completing monitor set and be protected in one walks.Enhance science and the practicality of health supervision device.
In said structure, processor hardware includes but not limited to single-chip microcomputer, CPU, ARM embedded system, GPU processor, FPGA system etc.
The present invention can realize location, meter step, heart rate detects in real time and intellectual analysis shows at LCD, and detection data to be transferred on server and intelligent terminal by wireless module and to realize fast alarms.The present invention breaks through Traditional Thinking by step function module installation at waist, and adopts the design's high accuracy meter to walk algorithm, greatly improves the accuracy of meter step.
What finally illustrate is, above preferred embodiment is only in order to illustrate technical scheme of the present invention and unrestricted, although by above preferred embodiment to invention has been detailed describing, but it will be appreciated by those skilled in the art that and should not depart from claims limited range to the various changes that it is made in the form and details.
Claims (10)
1. old people's intelligent monitoring device of high accuracy meter step, comprises wrist instrument; Described wrist instrument comprises the second processor and coupled pulse transducer, the second blue tooth interface, LCD display; It is characterized in that:
Described intelligent monitoring device comprises waist instrument, and described waist instrument comprises first processor and coupled meter walks sensor, high accuracy meter step computing unit, mobile communication delivery unit, the first blue tooth interface;
Described second blue tooth interface is connected with described first blue tooth interface Bluetooth communication;
Described high accuracy meter step computing unit is used for calculating the paces data of meter step sensor institute perception, obtains high accuracy meter step;
Described high accuracy meter step sends to wrist instrument by described second blue tooth interface, shows in described LCD display.
2. old people's intelligent monitoring device of high accuracy meter step according to claim 1, is characterized in that: it is 3-axis acceleration sensor that described meter walks sensor.
3. according to claim 1 high accuracy meter step old people's intelligent monitoring device, it is characterized in that: the described meter step data to the perception of meter step sensor institute calculates, the meter step data that acquisition high accuracy meter step comprises described meter step sensor obtains carries out combined filter, paces judgement is carried out to the meter step data after combined filter, to being judged to be that effective paces count.
4. according to claim 3 high accuracy meter step old people's intelligent monitoring device, it is characterized in that: described combined filter comprises the combination of morphologic filtering computing, medium filtering computing and average filtering operation, and described morphologic filtering computing is for removing baseline drift; Described medium filtering computing is for removing pulse signal and glitch noise, and described average filter computing is used for smooth signal, makes the wave character of signal more obvious.
5. old people's intelligent monitoring device of high accuracy meter step according to claim 4, is characterized in that: the paces data of described morphologic filtering computing to the sensor institute perception of meter step successively adopt the structural element of two kinds of different lengths to carry out filtering, comprising:
The structural element of g1, carries out filtering by the mean operation of opening and closing and make and break computing, forms first order Morphologic filters, with removing baseline drift, that is:
F1＝(f·g1оg1+fоg1·g1)/2
The structural element of g2, carries out filtering by the mean operation of opening and closing and make and break computing, forms second level Morphologic filters, with removing noise, that is:
F2＝(F1·g2оg2+F1оg2·g2)/2
Wherein, the paces data of f representative meter step sensor institute perception, F1 represents the signal after primary signal first time opening and closing operation, F2 represents the signal after second time opening and closing operation, g1 represents first order morphological structuring elements, g2 represents second level morphological structuring elements, and represent closed operation, o represents opening operation.
6. according to claim 4 high accuracy meter step old people's intelligent monitoring device, it is characterized in that: described medium filtering computing adopts to be preset the grow up paces data of method to the perception of meter step sensor institute of sliding window of little N3 of window and carry out filtering, remove pulse signal and glitch noise, that is:
F3'＝median{f3,N3},f3∈F3
Wherein, median{f3, N3} represent median filtering algorithm, f3 is the value in sliding window, this value derives from transmits the signal F3 that enters, and F3 is one of data F3' after the paces data f of meter step sensor institute perception or morphologic filtering computing, and F3 ' is the signal after medium filtering.
7. according to claim 4 high accuracy meter step old people's intelligent monitoring device, it is characterized in that: described average filter computing adopts the paces data of default moving window size N4 to the signal after medium filtering or the perception of meter step sensor institute to carry out filtering, smoothing to signal;
Wherein, F4 is the signal after the smothing filtering obtained, and m represents the filtering operation that to be averaged from m value of F3 ' signal.
8. according to claim 1 high accuracy meter step old people's intelligent monitoring device, it is characterized in that: described paces judgement is carried out to the meter step data after combined filter, to being judged to be that effective paces carry out counting and comprise: if the meter step data after combined filter meets one of following three conditions, then be judged to be effective paces, it counted:
Fixed threshold condition: the range value of the waveform of data after calculation of filtered, when range value exceedes reservation threshold, judges that this condition meets, and described reservation threshold is repeatedly the empirical value of data test.
F4 (m-1)≤standardvalue and F4 (m) >=standardvalue
Wherein, F4 (m-1) and F4 (m) represents the signal amplitude value in adjacent two moment, the empirical value that standardvalue many data tests obtain; Or
Wave crest and wave trough condition: when a pair adjacent crest and trough being detected, and when the difference of adjacent peaks and trough is greater than a certain standard value, judges that this condition meets; Or
Similarity condition: the similarity of data and standard signal after calculation of filtered, when similarity reaches a certain standard value, judges that this condition meets.
9. according to claim 1 high accuracy meter step old people's intelligent monitoring device, it is characterized in that: described paces judgement is carried out to the meter step data after combined filter, to being judged to be that effective paces carry out counting and comprise: if the meter step data after combined filter meets following three conditions simultaneously, then be judged to be effective paces, it counted:
Fixed threshold condition: the range value of the waveform of data after calculation of filtered, when range value exceedes reservation threshold, judges that this condition meets, and described reservation threshold is repeatedly the empirical value of data test.
F4 (m-1)≤standardvalue and F4 (m) >=standardvalue
Wherein, F4 (m-1) and F4 (m) represents the signal amplitude value in adjacent two moment, the empirical value that standardvalue many data tests obtain; With
Wave crest and wave trough condition: when a pair adjacent crest and trough being detected, and when the difference of adjacent peaks and trough is greater than a certain standard value, judges that this condition meets; With
Similarity condition: the similarity of data and standard signal after calculation of filtered, when similarity reaches a certain standard value, judges that this condition meets.
10. according to claim 1 high accuracy meter step old people's intelligent monitoring device, it is characterized in that: described similarity calculates according to the correlation coefficient of filtered data and standard signal, when correlation coefficient be greater than repeatedly test the empirical value similarvalue obtained time, namely work as R
sfduring >similarvalue, judge that similarity condition meets, wherein
represent the correlation coefficient of filtered data and standard signal, if S
nfor standard signal array, f4
nfor filtered data array, n≤N
p, N
prepresent filtered data array length.
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