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IoT Technologies for Health Care. 8th EAI International Conference, HealthyIoT 2021, Virtual Event, November 24-26, 2021, Proceedings

Research Article

GAIToe: Gait Analysis Utilizing an IMU for Toe Walking Detection and Intervention

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  • @INPROCEEDINGS{10.1007/978-3-030-99197-5_15,
        author={Ghazal Ershadi and Migyeong Gwak and Jane Liu and Gichan Lee and Afshin Aminian and Majid Sarrafzadeh},
        title={GAIToe: Gait Analysis Utilizing an IMU for Toe Walking Detection and Intervention},
        proceedings={IoT Technologies for Health Care. 8th EAI International Conference, HealthyIoT 2021, Virtual Event, November 24-26, 2021, Proceedings},
        proceedings_a={HEALTHYIOT},
        year={2022},
        month={3},
        keywords={Idiopathic toe walking Gait analysis Wearable sensor Inertial Measurement Unit (IMU) Machine learning},
        doi={10.1007/978-3-030-99197-5_15}
    }
    
  • Ghazal Ershadi
    Migyeong Gwak
    Jane Liu
    Gichan Lee
    Afshin Aminian
    Majid Sarrafzadeh
    Year: 2022
    GAIToe: Gait Analysis Utilizing an IMU for Toe Walking Detection and Intervention
    HEALTHYIOT
    Springer
    DOI: 10.1007/978-3-030-99197-5_15
Ghazal Ershadi1, Migyeong Gwak1,*, Jane Liu1, Gichan Lee1, Afshin Aminian2, Majid Sarrafzadeh1
  • 1: University of California, Los Angeles, Los Angeles
  • 2: Children’s Hospital of Orange County, 1201 West La Veta Avenue, Orange
*Contact email: mgwak@cs.ucla.edu

Abstract

Idiopathic toe walking (ITW) is a walking pattern in which a person habitually walks on their forefoot with the absence of heel contact during the gait cycle. Gait rehabilitation can be achieved through behavior modification by employing a wearable device and giving the user immediate feedback. In this paper, we introduce GAIToe, a real-time toe walking detection and intervention platform that remotely monitors walking patterns. GAIToe utilizes an Inertial Measurement Unit (IMU) located in the insole and incorporates a machine learning model to detect different walking, sitting, and standing behaviors. GAIToe identifies these activities with 88% accuracy and provides vibration feedback following consecutive toe strikes. It also provides an Android application to transmit the data and a visual context to monitor the walking patterns. For the preliminary evaluation of GAIToe, we collected activity samples from ten healthy subjects.

Keywords
Idiopathic toe walking Gait analysis Wearable sensor Inertial Measurement Unit (IMU) Machine learning
Published
2022-03-23
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-99197-5_15
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