A gait retraining feedback system based on wearable sensors

He, Zexia; Shen, Yang; Liu, Tao; Yi, Jingang; Ferreira, José Ribeiro

doi:10.1109/aim.2017.8014154

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Six Chronic Diseases and Corresponding Insole Systems1

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2023

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Cited by 2 publications

(3 citation statements)

References 12 publications

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“…[ 25 ] 2017 IMU Healthy 2 Lab Zexia He et al. [ 26 ] 2017 IMU Healthy 1 Lab Ficklsherer et al. [ 27 ] 2016 Force Transducer TKA 30 Lab Fung et al.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

The use of technology to support lifestyle interventions in knee osteoarthritis: A scoping review

Hamilton

Akhtar

Griffiths

et al. 2023

Osteoarthritis and Cartilage Open

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“…[ 25 ] 2017 IMU Healthy 2 Lab Zexia He et al. [ 26 ] 2017 IMU Healthy 1 Lab Ficklsherer et al. [ 27 ] 2016 Force Transducer TKA 30 Lab Fung et al.…”

Section: Resultsmentioning

confidence: 99%

“…Finally, Zexia et al. [ 26 ] described a gait retraining system that used KAM calculated by pressure sensors controlled through altering FPA, calculated using an IMU. Participants were able to decrease their KAM following FPA guided feedback.…”

Section: Resultsmentioning

confidence: 99%

The use of technology to support lifestyle interventions in knee osteoarthritis: A scoping review

Hamilton

Akhtar

Griffiths

et al. 2023

Osteoarthritis and Cartilage Open

View full text Add to dashboard Cite

“…Patients with KOA often exhibit poor postural balance and adopt specific gait strategies. Several critical indicators are used to monitor and analyze the motion abnormalities in KOA patients, including plantar pressure distribution [ 133 ], center of pressure (CoP) path [ 134 ], duration of gait phases, and knee adduction moment (KAM) [ 135 , 136 ]. These indicators are summarized in Table 7 [ 134 , 137 , 138 ].…”

Section: Six Chronic Diseases and Corresponding Insole Systemsmentioning

confidence: 99%

Insole Systems for Disease Diagnosis and Rehabilitation: A Review

Zhang,

Dai,

et al. 2023

Biosensors

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Some chronic diseases, including Parkinson’s disease (PD), diabetic foot, flat foot, stroke, elderly falling, and knee osteoarthritis (KOA), are related to orthopedic organs, nerves, and muscles. The interaction of these three parts will generate a comprehensive result: gait. Furthermore, the lesions in these regions can produce abnormal gait features. Therefore, monitoring the gait features can assist medical professionals in the diagnosis and analysis of these diseases. Nowadays, various insole systems based on different sensing techniques have been developed to monitor gait and aid in medical research. Hence, a detailed review of insole systems and their applications in disease management can greatly benefit researchers working in the field of medical engineering. This essay is composed of the following sections: the essay firstly provides an overview of the sensing mechanisms and parameters of typical insole systems based on different sensing techniques. Then this essay respectively discusses the three stages of gait parameters pre-processing, respectively: pressure reconstruction, feature extraction, and data normalization. Then, the relationship between gait features and pathogenic mechanisms is discussed, along with the introduction of insole systems that aid in medical research; Finally, the current challenges and future trends in the development of insole systems are discussed.

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A gait retraining feedback system based on wearable sensors

Cited by 2 publications

References 12 publications

The use of technology to support lifestyle interventions in knee osteoarthritis: A scoping review

The use of technology to support lifestyle interventions in knee osteoarthritis: A scoping review

Insole Systems for Disease Diagnosis and Rehabilitation: A Review

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