Classifications

• • 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
  • A61B5/112—Gait analysis
• • 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
  • A61B5/1036—Measuring load distribution, e.g. podologic studies
  • A61B5/1038—Measuring plantar pressure during gait
• • 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
  • A61B5/1113—Local tracking of patients, e.g. in a hospital or private home
  • A61B5/1114—Tracking parts of the body
• • 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
• • 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
• • 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
  • A61B5/1123—Discriminating type of movement, e.g. walking or running
• • A—HUMAN NECESSITIES
  • 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
  • A61B5/683—Means for maintaining contact with the body
  • A61B5/6831—Straps, bands or harnesses
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
  • A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
  • A61B5/7235—Details of waveform analysis
  • A61B5/725—Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
  • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
  • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
  • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
  • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
  • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
  • G01C21/1654—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments with electromagnetic compass
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
  • G01C22/00—Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers
  • G01C22/006—Pedometers
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
  • G06F17/10—Complex mathematical operations
  • G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B2562/00—Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
  • A61B2562/02—Details of sensors specially adapted for in-vivo measurements
  • A61B2562/0219—Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches

Definitions

• the invention relates to a system and method for detecting the walking of a person, or in other words the detection of a displacement of a person by a mode of locomotion constituted by a sequence of steps.
• the detection of a person's walking activity is information that makes it possible, for example, to estimate a person's energy expenditure, to evaluate a person's sedentary level, or to estimate the quality of a person's energy expenditure. or loss of functional ability after surgery or drug therapy.
• SUBSTITUTE SHEET (RULE 26) allows to study the stability of walking. It is not a question here of detecting a walking activity, but of analyzing or characterizing a walking activity of a person who is already known to be walking.
• a gait detection system of a person provided with a housing comprising a biaxial or triaxial motion sensor.
• the housing is adapted to be fixed on the upper part of the body of said person, so that a first measurement axis of said sensor coincides with the anteroposterior axis or the vertical axis of said body and a second axis of measurement of said sensor coincides with the medio-lateral axis of said body, said system being, furthermore, provided with means for analyzing the measurements delivered by said sensor.
• Said analysis means comprise:
• the time window is a slippery window.
• said motion sensor being triaxial, the first measurement axis of said sensor coincides with the anteroposterior axis of said body, the second measurement axis of said sensor coincides with the mediolateral axis of said body, and the third measurement axis of said sensor coincides with the vertical axis of said body, said detection means are adapted to detect a ratio substantially equal to two, between the dominant frequency of the signal of the first measurement axis and the dominant frequency of the second axis of measuring, or between the dominant frequency of the signal of the third measurement axis and the dominant frequency of the second measurement axis, or between the dominant frequency of a Euclidean norm of the measurement vector transmitted by said sensor and the dominant frequency of the signal of the second measuring axis.
• the system further comprises high-pass filters.
• the system further comprises band-pass filters, for example of frequency band between 0.5 and 10 Hz.
• band-pass filters for example of frequency band between 0.5 and 10 Hz.
• said analysis means are internal or external to said housing, and said motion sensor comprises wired or wireless transmission means for transmitting its measurements to said analysis means.
• the analysis means can be integrated in the housing or located on a remote basis, and the output signals of the housing, analyzed or not, can be transmitted with or without wire.
• Said motion sensor may be a biaxial or triaxial accelerometer, a biaxial or triaxial magnetometer, or a biaxial or triaxial gyro.
• the invention works with all these types of motion sensors.
• the sliding time window has a duration of five seconds, with a partial overlap of four seconds between two consecutive windows shifted by one second.
• said search means of a dominant frequency for the signals transmitted by the motion sensor are adapted to perform the dominant frequency search, in each time window, by spectral analysis.
• this spectral analysis may be of the spectrogram type.
• the spectrogram which uses the square of the Fourier transform module of the convolved signal to an apodization window, is a simple, reliable, and low-cost way of searching for a dominant frequency, ie the frequency corresponding to the maximum signal power.
• Said search means of a dominant frequency can be adapted to limit the search for a VML dominant frequency according to the second axis at frequencies between 0.25 Hz and 1 Hz.
• Said search means of a dominant frequency can be adapted to limit the search for a dominant frequency along the first axis, when it coincides with the antero-hitch-hopping axis, at frequencies within a predetermined range of frequencies. This frequency range can be limited by the dominant frequency along the second axis f M ⁇ _ Hz increased by 0.2 Hz and 3 Hz ([f ML +0.2; 3]).
• this range may be bounded by the dominant frequency along the second axis f M ⁇ _ Hz increased by 0.25 Hz and 2 Hz, ([f ML +0.25; 2]).
• Said search means of a dominant frequency can be adapted to limit the search for a dominant frequency along the first axis, when it coincides with the vertical axis, at frequencies within a predetermined range of frequencies.
• This frequency range can be limited by the dominant frequency along the second axis f M ⁇ _ Hz increased by 0.2 Hz and 3 Hz ([f M ⁇ _ + 0.2; 3]).
• Said search means of a dominant frequency can be adapted to limit the search for a dominant frequency for the Euclidean standard of the measurement vector transmitted by said motion sensor, at frequencies within a predetermined range of frequencies. This frequency range can be limited by the dominant frequency along the second axis f M ⁇ _ Hz increased by 0.2 Hz and 3 Hz ([f ML +0.2; 3]).
• said detection means are adapted to detect a ratio of said dominant frequencies substantially equal to two, to a precision, when, moreover, at least on one axis, the power of the signal, at least one frequency , is greater than a threshold.
• Such a ratio is determined or exploited only for windows having, on at least one axis, at least one frequency whose power is greater than a determined threshold, this threshold possibly being called a power threshold.
• This power threshold is determined a priori, or adjusted experimentally, for example during a test phase.
• This power condition of at least one frequency can be applied to at least one axis, but also to all axes. Note that when this power condition is applied on different axes, each power threshold may be different from each other.
• said determination means are adapted to determine the ratio of the dominant frequencies, corresponding to a given time window, when, on at least one axis, the dominant frequency has a power greater than a threshold power.
• This threshold condition can be applied only to the dominant frequency, but also to other defined frequencies or frequency bands.
• this threshold power criterion can also be applied to the Euclidean norm of the vector of measurements. For each time window, then check the frequency or frequencies, for example the dominant frequency, have a power greater than a power threshold.
• This power threshold can be fixed a priori or by previously determining a power in a time interval during which nothing happens, for example during anatomical calibration.
• said housing is adapted to be fixed on the torso or on the sacrum of said person.
• the amplitude of the oscillations of the trunk is higher, which improves the accuracy of the system.
• the fixation at the level of the sacrum is particularly easy and discreet, for example by means of a belt.
• a method for detecting a person's walking from measurements made by a biaxial or triaxial motion sensor, of movements along a first measurement axis of said sensor coinciding with the anteroposterior axis or the vertical axis of the body of said person and along a second axis measuring said sensor coinciding with the medio-lateral axis of said body, in which:
• the measurement signals delivered by said motion sensor are processed over a time window, said processing comprising a search for a dominant frequency in said signals and
• the step of said person is detected when a ratio between the dominant frequency of the signal of the first measurement axis and the dominant frequency of the second measurement axis, or between the dominant frequency of a Euclidean norm of the vector of measurements transmitted by said sensor and the dominant frequency of the signal of the second measurement axis, is substantially equal to two.
• the processing is performed on a sliding time window.
• FIG. 1 schematically illustrates an embodiment of a system, according to one aspect of the invention
• FIG. 3 illustrates an example of measurements made by a system according to FIG. 1, in which the motion sensor is a biaxial accelerometer;
• FIGS. 4 and 5 illustrate the operation of the analysis means
• FIGS. 6a and 6b illustrate a first mode of implementation of the system according to one aspect of the invention
• FIGS. 7a, 7b and 7c illustrate a second mode of implementation of the system according to one aspect of the invention
• FIGS. 8a and 8b illustrate a third mode of implementation of the system according to one aspect of the invention.
• FIGS. 9a and 9b illustrate a fourth mode of implementation of the system according to one aspect of the invention.
• FIGS. 10a and 10b illustrate a fifth mode of implementation of the system according to one aspect of the invention.
• the elements having the same references are similar.
• a person's walking detection system comprises a BT housing comprising a biaxial or triaxial CM motion sensor.
• the housing BT is adapted to be fixed on the upper part of the body of said person, in this case by means of a resilient fastening belt CEF, so that a first measurement axis of said motion sensor coincides with the anterior-posterior axis AP or the vertical axis VT of said body and a second measurement axis of said motion sensor coincides with the medio-lateral axis ML of said body.
• any other means of attachment may be suitable.
• This coincidence can, for example, be made by anatomical calibration, for example by asking the person to whom the BT housing was fixed to stand as straight as possible for a few seconds against a wall, the system, in a known manner , determines the rotation matrix to be applied to the measurements to deliver measurements brought back to the medio-lateral axes ML, anteroposterior AP or vertical VT.
• the motion sensor CM is also provided with a transmission module MTR for transmitting the measurements, in this example by wireless transmission, to an external station SE, in this case a laptop.
• the motion sensor may, for example, be a biaxial or triaxial accelerometer, a biaxial or triaxial magnetometer, or a biaxial or triaxial gyro.
• the motion sensor CM will be a biaxial accelerometer whose first measurement axis coincides with the anteroposterior axis AP of the body of the person, and the second axis of measurement coincides with the medial-lateral axis ML of the body of the person.
• the second measurement axis of the accelerometer may coincide with the medial-lateral axis ML of the body of the person, and the first measurement axis may coincide with the vertical axis VT of the body of the person.
• the portable computer SE comprises an analysis module MA of the data transmitted by the accelerometer CM.
• the analysis module can be integrated into the LV box.
• the analysis module is adapted to sample the signals received from the accelerometer CM at a sampling frequency less than or equal to 1 kHz, and typically of the order of 10 to 200 Hz.
• the analysis module MA comprises a processing module MT for processing the measurement signals delivered by the accelerometer CM.
• the detection module is adapted to detect a ratio substantially equal to two, between the dominant frequency of the signal of the first measurement axis and the dominant frequency of the second measurement axis, or between the dominant frequency of the third axis signal. measurement and the dominant frequency of the second measurement axis, or between the dominant frequency of a Euclidean norm of the measurement vector transmitted by said sensor and the dominant frequency of the signal of the second measurement axis. We then have an improved detection precision.
• a ratio or ratio substantially equal to 2 a ratio for example between 1.7 and 2.3, and preferably between 1.9 and 2.1.
• This ratio can be predetermined, but also adjusted experimentally, especially during a test phase. We then analyze precisely the different values taken by this ratio when the person walks, and we determine the critical value that will be implemented in the algorithm. This determination can be made statistically, considering the risks associated with false positives (the device indicates that the person is walking when it is not working) or false negatives (the device indicates that the person does not 'she walks).
• the processing module MT may comprise high-pass filters, FPH for deleting the respective continuous components of the signals transmitted by the accelerometer CM, to be able to accurately detect the dominant frequency.
• the processing module MT may also include bandpass filters so as to greatly limit the influence of noises or frequencies of signals unrelated to walking.
• the processing module MT comprises a search module of a dominant frequency MRFD for the signals transmitted by the motion sensor, by spectral analysis.
• Spectral analysis which consists in estimating the signal power as a function of frequency, is a known, simple and inexpensive way of calculating to search for a dominant frequency in a signal.
• dominant frequency is meant the frequency which corresponds to the maximum of the power density of the signal.
• the spectral analysis can be carried out using a Fourier transform, but also other techniques known to those skilled in the art, for example a wavelet transform, a technique better adapted to nonstationary signals.
• the analysis module MA also comprises a detection module MD of the step of the person when a ratio between the dominant frequency of the signal of the first measurement axis and the dominant frequency of the second measurement axis, or between the dominant frequency of the a Euclidean norm of the vector of measurements transmitted by said sensor and the dominant frequency of the signal of the second measurement axis, is substantially equal to two.
• the present invention operates without the need for a physical calibration of the motion sensor CM, or, in other words, a system according to the invention operates from the raw data expressed in numerical unit or in volts and the knowledge of the gains and offsets of the CM motion sensor is not essential. If we decide not to transform the volts into a physical unit (for example m / s 2 for an accelerometer) the notion of minimum power threshold can be decided from a measurement of the person in a state of rest and not more from a kinematic data.
• the medio-lateral axis ML of the body is oriented from the left part of the body to the right part of the body
• the anteroposterior axis AP is oriented from the rear part of the body towards the front part of the body
• the vertical axis is oriented from the upper body to the lower part of the body.
• the housing can be disposed at the torso, or at the level of the sacrum.
• the band-pass filter FPB may, for example be a Butterworth filter of order 4 filtering in the frequency band between 0.5 and 10 Hz, particularly well suited to walking.
• the signals are divided into analysis time windows, the time windows being preferably sliding time windows, for example in five-second windows, with a partial overlap of four seconds between two consecutive windows shifted by one second. For each time window, it then seeks dominant frequencies of signals.
• the search module of a MRFD dominant frequency by spectral analysis of spectrogram type can be adapted to limit the search for a dominant frequency along the first axis f M ⁇ _ at frequencies between 0.25 Hz and 1 Hz.
• the search module for a dominant frequency MRFD by spectral analysis can also be adapted to limit the search for a dominant frequency along the first axis, when it coincides with the anteroposterior axis AP, at frequencies between the dominant frequency along the second axis f M ⁇ _ Hz increased by 0.2 Hz and 3 Hz, or at frequencies between the dominant frequency along the second axis f M ⁇ _ Hz increased by 0.25 Hz and 2 Hz ([f M ⁇ _ + 0.25 ;
• the search module of a dominant frequency MRFD by spectral analysis can also be adapted to limit the search for a dominant frequency along the first axis, when it coincides with the vertical axis VT, at frequencies between the frequency dominant according to the second axis f M ⁇ _ Hz increased by 0.2 Hz and 3 Hz.
• the module for finding a MRFD dominant frequency by spectral analysis may also be adapted to limit the search for a dominant frequency for the Euclidean norm of the vector of measurements transmitted by said CM motion sensor, at frequencies between the dominant frequency along the second axis f M ⁇ _ Hz increased by 0.2 Hz and 3 Hz.
• FIG. 3 represents an example of signals S M 1 and S A p transmitted by a housing BT according to one aspect of the invention, provided with a biaxial accelerometer CM, whose first measurement axis coincides with the anteroposterior axis. AP, and the second measurement axis coincides with the medio-lateral axis ML, as a function of time.
• the BT housing is, for example, disposed at the sacrum of the person, whose activity is monitored.
• FIG. 4 represents, for the case of the data of FIG. 3, the dominant frequencies f M ⁇ _ and f A p as a function of time, corresponding to the signals S M ⁇ _ and S AP , the dominant frequencies f M ⁇ _ and f A p being calculated by the search module of a dominant frequency MRFD, by sliding window.
• FIG. 5 represents, in the case of FIGS. 3 and 4, the calculation by the MD detection module from the ratio of the dominant frequencies f M ⁇ _ and f AP .
• the system detects a walking activity between the instants corresponding to the initial instant 0 s, and the instant corresponding to 182 s after the initial instant, and a walking activity starting from the instant corresponding to 221 s after the initial moment.
• a user wears a gait detection system according to one aspect of the invention, with which it occupies different postures, immobile or moving, during different tests.
• the measurements are made at a sampling rate of 200 Hz. These data are grouped together on a sliding window, with a duration equal to 10 s, with an overlap of 90% between two consecutive windows.
• Bandpass filtering [0.1 Hz; 10 Hz] is applied to these measurements by a Butterworth NR filter of order 4.
• a spectral analysis of each window is performed by calculating the square of the Fourier transform module of the product between the signal measured by the apodization window, to achieve a spectrogram. The dominant frequency f M ⁇ _ on the second axis is determined on each window.
• the dominant frequency is determined in a respective preferred frequency value range: f M ⁇ _ between 0.25 Hz and 1 Hz, and f A p between f ML +0.25 and 2 Hz.
• Figures 6a and 6b illustrate a first example.
• Figure 6a illustrates a registration with a system according to an aspect of the invention worn on the belt. The detection is activated regardless of the power of the signal measured along the medio-lateral axis ML.
• FIG. 6a shows dominant frequencies f M ⁇ _ and f A p as a function of the indexes of windows. These are the dominant frequencies determined, for each time window, respectively along the medio-lateral axes ML and anterior-posterior AP.
• FIG. 6b represents the ratio or ratio, for each time window, between the dominant frequencies f A p and f M ⁇ _- In this example, the person only walks between the time windows 160 and 210.
• the ratio corresponding to these time windows is around the value 2.
• This test therefore makes it possible to determine a threshold, substantially equal to 2, in this case, for example 1.9, above which the person is considered to walk.
• This threshold can be determined manually, according to this type of test, or by known statistical analysis techniques, to estimate the risks of false positives and false negatives.
• the threshold is substantially equal to 2, ie close to 2, but not strictly equal to 2, an adjustment that can be made during experimental tests.
• This adjustment can be manual or automatically developed, for example by determining a statistical distribution of the ratio between f A p and f M ⁇ _ and by estimating certain parameters of this distribution, for example the mean and the standard deviation in the case where the distribution is assumed normal.
• Figures 7a, 7b and 7c illustrate a second example in which the gait detection system is worn on the belt.
• a threshold the power of the measured signal is imposed, for example on the signal measured along the medio-lateral axis ML.
• This power is represented in figure 7a of the power as a function of the window index.
• the power unit here is the gravity constant squared This curve thus represents the power of the dominant frequency determined, along the medio-lateral axis ML, for each time window.
• FIG. 7b only the dominant frequencies f A p along the antero-posterior axis AP are reported for time windows having a signal measured along the medio-lateral axis ML, the power of which is greater than the threshold mentioned.
• the user walks between the time windows 155 and 210, as well as between the time windows 102 and 107.
• FIG. 7c for each window corresponding to a step of the user, a substantially equal ratio is obtained. at 2, that is to say between 1.8 and 2.2.
• the threshold could be set at 1 .8 or 1 .9.
• the power criterion applies either to the signal measured along the medio-lateral axis ML, or to the signal measured along the anteroposterior axis AP, or to these two signals, the thresholds then being different.
• FIGS. 8a and 8b illustrate a third example for which FIG. 8b represents the ratio of the dominant frequency of a Euclidean norm of the vector of measurements transmitted by said sensor CM and the dominant frequency f M ⁇ _ of the signal of the second measurement axis.
• FIGS. 8a and 8b illustrate a third example for which FIG. 8b represents the ratio of the dominant frequency of a Euclidean norm of the vector of measurements transmitted by said sensor CM and the dominant frequency f M ⁇ _ of the signal of the second measurement axis.
• Two other embodiments respectively illustrated in Figures 9a, 9b and 10a, 10b, with a system respectively fixed to the belt and the torso.
• the present invention allows, at reduced cost, to detect with great precision, a walking activity of a person.
• the present invention has particularly described the detection of a walking phase, it can be applied to a phase of the frequency ranges of search for a dominant frequency are then adjusted.
• the present invention operates without necessarily requiring physical calibration of the motion sensor.

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