CN110786863B - Pedestrian gait detection method based on mobile device - Google Patents
Pedestrian gait detection method based on mobile device Download PDFInfo
- Publication number
- CN110786863B CN110786863B CN201911080535.3A CN201911080535A CN110786863B CN 110786863 B CN110786863 B CN 110786863B CN 201911080535 A CN201911080535 A CN 201911080535A CN 110786863 B CN110786863 B CN 110786863B
- Authority
- CN
- China
- Prior art keywords
- frequency
- coordinate system
- under
- mobile equipment
- pedestrian
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
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
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
- A61B5/6898—Portable consumer electronic devices, e.g. music players, telephones, tablet computers
-
- 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
-
- 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
- A61B5/7253—Details of waveform analysis characterised by using transforms
- A61B5/7257—Details of waveform analysis characterised by using transforms using Fourier transforms
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Animal Behavior & Ethology (AREA)
- Veterinary Medicine (AREA)
- Pathology (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Biophysics (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Physiology (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Psychiatry (AREA)
- Signal Processing (AREA)
- Multimedia (AREA)
- Mathematical Physics (AREA)
- Dentistry (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Measurement Of Length, Angles, Or The Like Using Electric Or Magnetic Means (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The invention discloses a pedestrian gait detection method based on mobile equipment, which comprises the following steps: a. collecting sensor data of the mobile equipment in motion under a mobile equipment coordinate system; b. calculating a rotation matrix of the mobile equipment according to the sensor data of the mobile phone, and converting the triaxial accelerometer data under the coordinate system of the mobile equipment into a geographic coordinate system; c. extracting a vertical component of the acceleration under the geographic coordinate system, and acquiring signal intensity; d. finding out the frequency of the first 2 bits with the maximum signal intensity in the frequency range of [0.5,4] Hz, and determining whether the ratio of the larger frequency to the smaller frequency between the two is in the range of [1.5,2.5 ]; e. the specific step detection time can be determined by using a peak detection mode. According to the method, the information of relative motion between the pedestrian and the mobile phone is filtered out according to the acceleration information frequency characteristic of walking of the pedestrian, effective data are finally extracted for gait detection, and the gait detection accuracy is improved.
Description
Technical Field
The invention relates to the technical field of positioning based on mobile equipment, in particular to a pedestrian gait detection method based on the mobile equipment.
Background
The current positioning technology of the mobile device needs to rely on a Pedestrian Dead Reckoning (PDR) system to a great extent, and such a scheme that a beacon node is not required to be pre-installed in a building, and the step length and the direction of a Pedestrian are calculated by using an intrinsic inertial sensor (such as an acceleration sensor, a gyroscope, a magnetometer and the like) of the mobile device, so as to estimate the track of the person who goes out in the building.
Pedestrian walking is a periodic motion process with alternating feet, and the periodicity of the periodic motion process is reflected on inertial sensor data of the mobile equipment, such as acceleration, a gyroscope and the like. A commonly used algorithm in gait detection is a wave crest/zero crossing detection algorithm based on accelerometer data, and has the advantages of simple algorithm implementation, small calculated amount and convenient real-time detection.
At present, the accuracy of hardware equipment of the inertial sensor of the mobile equipment is not high generally, the models of the sensors equipped with different equipment are different, and the collected acceleration signals contain noise due to the random change of the walking state of pedestrians, so that the accuracy of the traditional detection algorithm is not high. On the other hand, the pedestrian is in a random state in the process of using the mobile device, and may have unfixed relative motion with the device, especially in the case that the pedestrian holds the device to swing around, so that the motion information of the pedestrian is polluted by the relative change information, and the detection omission condition occurs in the gait detection.
Disclosure of Invention
The present invention is directed to a pedestrian gait detection method based on a mobile device, so as to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: a pedestrian gait detection method based on mobile equipment comprises the following steps:
a. collecting sensor data of the mobile equipment in motion under a coordinate system of the mobile equipment, wherein the sensor data comprises a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer;
b. calculating a rotation matrix of the mobile equipment according to sensor data of the mobile equipment, and converting triaxial accelerometer data under a coordinate system of the mobile equipment into a geographic coordinate system;
c. extracting a vertical component of the acceleration under the geographic coordinate system, namely a z-axis component of the geographic coordinate system, performing spectrum analysis on the vertical component by adopting fast Fourier transform, and acquiring signal intensity corresponding to each frequency with the frequency between [0 and sampling frequency/2 ];
d. finding out the frequency of the first 2 bits with the maximum signal intensity within the frequency range of [0.5,4] Hz, determining whether the ratio of the larger frequency to the smaller frequency between the two frequencies is within the range of [1.5,2.5], when the frequency ratio is within the range of [1.5,2.5], obtaining the signal under the corresponding frequency by using the moving frequency of the pedestrian as the larger frequency, performing band-pass filtering on the vertical component of the accelerometer under the geographic coordinate system, and when the frequency ratio is not within the range of [1.5,2.5], obtaining the signal under the corresponding frequency by using the moving frequency of the pedestrian as the smaller frequency, and performing band-pass filtering on the vertical component of the accelerometer under the geographic coordinate system;
e. and obtaining a time domain change curve under the corresponding frequency through inverse Fourier transform, performing wave crest detection on the filtered vertical component data of the accelerometer under a geographic coordinate system, and determining the specific step detection time by using a wave crest detection mode.
Compared with the prior art, the invention has the beneficial effects that: according to the pedestrian gait detection method based on the mobile device, the accelerometer data in the vertical direction is adopted, interference and shaking in the horizontal direction of the movement of the pedestrian can be avoided, the frequency spectrum characteristic of the accelerometer data after fast Fourier change is filtered, the noise of sensor hardware equipment is effectively filtered, and the gait detection can be effectively achieved by 95% of accuracy under the conditions that the mobile device is normally held by a hand, the body side swings, the inside of a bag, a pocket and the like.
Drawings
FIG. 1 is a schematic diagram of a moving coordinate system according to the present invention.
FIG. 2 is a schematic diagram of a geographic coordinate system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a technical scheme that:
example 1:
a pedestrian gait detection method based on a mobile device comprises the following steps:
a. collecting sensor data of the mobile equipment in motion under a coordinate system of the mobile equipment, wherein the sensor data comprises a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer;
b. calculating a rotation matrix of the mobile equipment according to sensor data of the mobile equipment, and converting triaxial accelerometer data under a coordinate system of the mobile equipment into a geographic coordinate system;
c. extracting a vertical component of the acceleration under the geographic coordinate system, namely a z-axis component of the geographic coordinate system, performing spectrum analysis on the vertical component by adopting fast Fourier transform, and acquiring signal intensity corresponding to each frequency with the frequency between [0 and sampling frequency/2 ];
d. finding out the frequency of the first 2 bits with the maximum signal intensity within the frequency range of [0.5,4] Hz, determining whether the ratio of the larger frequency to the smaller frequency between the two frequencies is within the range of [1.5,2.5], when the frequency ratio is within the range of [1.5,2.5], obtaining the signal under the corresponding frequency by using the moving frequency of the pedestrian as the larger frequency, performing band-pass filtering on the vertical component of the accelerometer under the geographic coordinate system, and when the frequency ratio is not within the range of [1.5,2.5], obtaining the signal under the corresponding frequency by using the moving frequency of the pedestrian as the smaller frequency, and performing band-pass filtering on the vertical component of the accelerometer under the geographic coordinate system;
e. and obtaining a time domain change curve under the corresponding frequency through inverse Fourier transform, performing peak detection on the filtered vertical component data of the accelerometer under a geographic coordinate system, and determining the specific step detection time by using a peak detection mode.
Example 2:
converting accelerometer sensor data under a mobile equipment coordinate system into a horizontal component and a vertical component under a geographic coordinate system according to the rotation matrix;
and extracting a vertical component of the accelerometer under a geographic coordinate system, performing spectrum analysis on the vertical component by adopting Fast Fourier Transform (FFT), and acquiring an amplitude value corresponding to each frequency between [0 and sampling frequency ]. Finding out the frequency corresponding to the maximum 2 amplitudes, and determining whether the ratio of the larger frequency to the smaller frequency between the two satisfies the relation of 2 times. If the pedestrian advancing frequency is met, reserving a larger frequency as the pedestrian advancing frequency, and performing band-pass filtering on the vertical component of the accelerometer under the geographic coordinate system; if the pedestrian heading frequency does not meet the requirement, reserving a smaller frequency as the pedestrian heading frequency, and performing band-pass filtering on the vertical component of the accelerometer under the geographic coordinate system;
and performing peak detection on the filtered vertical component data of the accelerometer in a geographic coordinate system to determine a gait detection time point.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (1)
1. A pedestrian gait detection method based on mobile equipment is characterized by comprising the following steps: the method comprises the following steps:
a. collecting sensor data of the mobile equipment in motion under a coordinate system of the mobile equipment, wherein the sensor data comprises a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer;
b. calculating a rotation matrix of the mobile equipment according to sensor data of the mobile equipment, and converting triaxial accelerometer data under a coordinate system of the mobile equipment into a geographic coordinate system;
c. extracting a vertical component of the acceleration under the geographic coordinate system, namely a z-axis component of the geographic coordinate system, performing spectrum analysis on the vertical component by adopting fast Fourier transform, and acquiring signal intensity corresponding to each frequency with the frequency between [0 and sampling frequency/2 ];
d. finding out the frequency of the first 2 bits with the maximum signal intensity within the frequency range of [0.5,4] Hz, determining whether the ratio of the larger frequency to the smaller frequency between the two frequencies is within the range of [1.5,2.5], when the frequency ratio is within the range of [1.5,2.5], obtaining the signal under the corresponding frequency by using the moving frequency of the pedestrian as the larger frequency, performing band-pass filtering on the vertical component of the accelerometer under the geographic coordinate system, and when the frequency ratio is not within the range of [1.5,2.5], obtaining the signal under the corresponding frequency by using the moving frequency of the pedestrian as the smaller frequency, and performing band-pass filtering on the vertical component of the accelerometer under the geographic coordinate system;
e. and obtaining a time domain change curve under the corresponding frequency through inverse Fourier transform, performing peak detection on the filtered vertical component data of the accelerometer under a geographic coordinate system, and determining the specific step detection time by using a peak detection mode.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911080535.3A CN110786863B (en) | 2019-11-07 | 2019-11-07 | Pedestrian gait detection method based on mobile device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911080535.3A CN110786863B (en) | 2019-11-07 | 2019-11-07 | Pedestrian gait detection method based on mobile device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110786863A CN110786863A (en) | 2020-02-14 |
| CN110786863B true CN110786863B (en) | 2022-06-14 |
Family
ID=69443193
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911080535.3A Active CN110786863B (en) | 2019-11-07 | 2019-11-07 | Pedestrian gait detection method based on mobile device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110786863B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111428690B (en) * | 2020-04-21 | 2022-08-09 | 桂林电子科技大学 | Identity authentication method based on gait signal topology analysis |
| CN111586580A (en) * | 2020-04-29 | 2020-08-25 | 杭州十域科技有限公司 | Position event capturing method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2013022188A (en) * | 2011-07-20 | 2013-02-04 | Nippon Telegr & Teleph Corp <Ntt> | Gait analyzing method, gait analyzer, and program of the same |
| CN105180959A (en) * | 2015-09-01 | 2015-12-23 | 北京理工大学 | Anti-interference step counting method for wrist type step counting devices |
| CN106225786A (en) * | 2016-08-15 | 2016-12-14 | 北京理工大学 | A kind of adaptive pedestrian navigation system zero-speed section detecting method |
| CN107966161A (en) * | 2017-11-09 | 2018-04-27 | 内蒙古大学 | Walking detection method based on FFT |
| CN108413957A (en) * | 2017-12-06 | 2018-08-17 | 上海交通大学 | The method for carrying out pedestrian's course estimation under multiple carrying mode using mobile terminal |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB0602127D0 (en) * | 2006-02-02 | 2006-03-15 | Imp Innovations Ltd | Gait analysis |
-
2019
- 2019-11-07 CN CN201911080535.3A patent/CN110786863B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2013022188A (en) * | 2011-07-20 | 2013-02-04 | Nippon Telegr & Teleph Corp <Ntt> | Gait analyzing method, gait analyzer, and program of the same |
| CN105180959A (en) * | 2015-09-01 | 2015-12-23 | 北京理工大学 | Anti-interference step counting method for wrist type step counting devices |
| CN106225786A (en) * | 2016-08-15 | 2016-12-14 | 北京理工大学 | A kind of adaptive pedestrian navigation system zero-speed section detecting method |
| CN107966161A (en) * | 2017-11-09 | 2018-04-27 | 内蒙古大学 | Walking detection method based on FFT |
| CN108413957A (en) * | 2017-12-06 | 2018-08-17 | 上海交通大学 | The method for carrying out pedestrian's course estimation under multiple carrying mode using mobile terminal |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110786863A (en) | 2020-02-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9228836B2 (en) | Inference of vehicular trajectory characteristics with personal mobile devices | |
| CN104266894B (en) | A kind of mine microquake signal preliminary wave moment extracting method based on correlation analysis | |
| CN110786863B (en) | Pedestrian gait detection method based on mobile device | |
| CN105758404B (en) | The real-time location method and system of smart machine | |
| CN105716604A (en) | Mobile robot indoor positioning method and system based on geomagnetic sequences | |
| WO2017000563A1 (en) | Real-time location method and system for intelligent device, and determination method for movement posture of mobile phone | |
| WO2016071759A1 (en) | Pedestrian dead reckoning position tracker | |
| Li et al. | Time-varying parameter identification of bridges subject to moving vehicles using ridge extraction based on empirical wavelet transform | |
| CN109612463B (en) | Pedestrian navigation positioning method based on lateral speed constraint optimization | |
| Chen et al. | Sensing strides using EMG signal for pedestrian navigation | |
| CN105180959A (en) | Anti-interference step counting method for wrist type step counting devices | |
| CN108089225A (en) | A kind of earthquake magnitude Method of fast estimating based on separate unit station first arrival P ripples | |
| JP2004085511A (en) | Method and system for estimating moving speed and position of moving body and navigation system | |
| Kaloop et al. | Analysis of the dynamic behavior of structures using the high-rate GNSS-PPP method combined with a wavelet-neural model: Numerical simulation and experimental tests | |
| CN111693283B (en) | Bearing unsteady state fault feature non-rotating speed extraction method | |
| Wang et al. | Improved step detection and step length estimation based on pedestrian dead reckoning | |
| US20180035382A1 (en) | Method and Device for Activating and Deactivating Geopositioning Devices in Moving Vehicles | |
| CN106323330A (en) | Non-contact-type step count method based on WiFi motion recognition system | |
| CN104605859A (en) | Indoor navigation gait detection method based on mobile terminal sensor | |
| CN111405469B (en) | Mine earthquake monitoring system based on mobile phone mobile sensing network and crowd-sourcing positioning method | |
| US20150032033A1 (en) | Apparatus and method for identifying movement in a patient | |
| CN115127581B (en) | Running data monitoring method and device, terminal equipment and storage medium | |
| CN109238301A (en) | A kind of step-recording method based on mobile phone acceleration and gyro sensor | |
| CN116943130A (en) | Counting method, counting device, counting equipment and storage medium | |
| CN112377153B (en) | Method for acquiring stroke and stroke frequency of beam-pumping unit based on acceleration sensor |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |