Smartphone IMU Sensors for Human Identification through Hip Joint Angle Analysis

Gait monitoring using hip joint angles offers a promising approach for person identification, leveraging the capabilities of smartphone inertial measurement units (IMUs). This study investigates the use of smartphone IMUs to extract hip joint angles for distinguishing individuals based on their gait...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2024-07, Vol.24 (15), p.4769
Main Authors: Andersson, Rabé, Bermejo-García, Javier, Agujetas, Rafael, Cronhjort, Mikael, Chilo, José
Format: Article
Language:English
Subjects:
Accelerometry - instrumentation
Accelerometry - methods
Adult
Algorithms
Data mining
Female
Gait
Gait - physiology
Gait Analysis - instrumentation
Gait Analysis - methods
Hip Joint - physiology
human motion analysis
Humans
IMU sensors
Machine Learning
machine learning classification
Male
Neural networks
person recognition
Sensors
Smart phones
Smartphone
smartphone sensors
Smartphones
Walking - physiology
Young Adult
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Summary:Gait monitoring using hip joint angles offers a promising approach for person identification, leveraging the capabilities of smartphone inertial measurement units (IMUs). This study investigates the use of smartphone IMUs to extract hip joint angles for distinguishing individuals based on their gait patterns. The data were collected from 10 healthy subjects (8 males, 2 females) walking on a treadmill at 4 km/h for 10 min. A sensor fusion technique that combined accelerometer, gyroscope, and magnetometer data was used to derive meaningful hip joint angles. We employed various machine learning algorithms within the WEKA environment to classify subjects based on their hip joint pattern and achieved a classification accuracy of 88.9%. Our findings demonstrate the feasibility of using hip joint angles for person identification, providing a baseline for future research in gait analysis for biometric applications. This work underscores the potential of smartphone-based gait analysis in personal identification systems.
ISSN:1424-8220
1424-8220
DOI:10.3390/s24154769