A real time study of the human equilibrium using an instrumented insole with 3 pressure sensors

Ghaida, Hussein Abou; Mottet, S.; Goujon, Jean-Marc

doi:10.1109/embc.2014.6944739

Cited by 7 publications

(7 citation statements)

References 13 publications

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“…Significantly, gait features can comprehensively reflect and demonstrate the coordination of CNS, PN and lower limbs [8]. Hence, through analyzing these gait patterns, related results, like plantar pressure distribution, can contribute to orthopedic and neurologic lesion monitoring, like foot ulceration and loss of dopamine [9], to provide ample information for recovery.…”

Section: Fig 1 Demonstration Of Diseases; Sensing Techniques and Curr...mentioning

confidence: 99%

Insole Systems for Disease Diagnosis and Rehabilitation

Gao¹,

Zhang²,

Wang³

et al. 2022

Preprint

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Neurological and orthopedic chronic diseases are proven to numerous complications and related dysfunction for patients, and are leading factors of death and disability. Conventional methods of diagnosis and rehabilitation are conducted at hospitals. However, due to the aging society and controversial privacy protection, traditional methods implemented in medical institutions have faced numerous challenges. Hence, internet of healthcare things (IoHT) based techniques have recently begun to be implemented. In order to provide flexible utilization and secure privacy for patients, wearable devices, like whole body devices based on electromyography (EMG) and radio frequency identification (RFID) insole systems, based on gait-analysis were applied. Among these techniques, insole systems for medical analysis are more suitable, because the root cause of neurologic and orthopedic chronic diseases are directly related to several gait characteristics. Neurologic and orthopedic chronic diseases are caused by lesions of the central nervous system (CNS), peripheral nerves (PN) and orthopedic limbs, similarly gait features are comprehensive results generated by the coordination of CNS, PN and lower limbs However, owing to lack of standards for instrumentation and the knowledge gap between engineering and pathogenic mechanism, the medical application of insole systems and the development of IoHT are hindered. This article is presented to address these issues. In this context, five plantar sensing mechanisms and their related products will be overviewed. Next, pathogenic mechanisms and pathological gait features of six representative chronic neurologic diseases will be displayed. Likewise, the development of corresponding insole systems for supervision and recovery for these diseases will be reviewed as well. Finally, challenges and future trends for current work will be discussed. This article will not only provide guidelines for the design of insole systems targeted for specific diseases but will also inspire the innovation of novel ideas. <br>

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Section: Fig 1 Demonstration Of Diseases; Sensing Techniques and Curr...mentioning

confidence: 99%

Insole Systems for Disease Diagnosis and Rehabilitation

Gao¹,

Zhang²,

Wang³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…A common solution was created with force-sensitive resistors placed at specific locations across the foot. This has been effectively used to detect pressure for a much lower cost than commercial solutions and allows for significant customizability [ 40 , 41 , 42 , 43 , 44 , 45 ].…”

Section: Introductionmentioning

confidence: 99%

Empirical Study on Human Movement Classification Using Insole Footwear Sensor System and Machine Learning

Anderson

Choffin

Jeong

et al. 2022

Sensors

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This paper presents a plantar pressure sensor system (P2S2) integrated in the insoles of shoes to detect thirteen commonly used human movements including walking, stooping left and right, pulling a cart backward, squatting, descending, ascending stairs, running, and falling (front, back, right, left). Six force sensitive resistors (FSR) sensors were positioned on critical pressure points on the insoles to capture the electrical signature of pressure change in the various movements. A total of 34 adult participants were tested with the P2S2. The pressure data were collected and processed using a Principal Component Analysis (PCA) for input to the multiple machine learning (ML) algorithms, including k-NN, neural network and Support-Vector Machine (SVM) algorithms. The ML models were trained using four-fold cross-validation. Each fold kept subject data independent from other folds. The model proved effective with an accuracy of 86%, showing a promising result in predicting human movements using the P2S2 integrated in shoes.

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“…In-shoe systems can overcome the usability limitations of platforms, enabling measurements of plantar pressure distribution within a shoe, in indoor and outdoor environments. In [ 5 , 6 , 7 ], three insoles with, respectively, 10, 4, and 3 sensors are used to measure the COP for the assessment of balance. All these applications are based on force sensing resistors (FSRs), whose hard structure can reduce the comfort for the user.…”

Section: Introductionmentioning

confidence: 99%

Design and Validation of an E-Textile-Based Wearable Sock for Remote Gait and Postural Assessment

Amitrano

Coccia

Ricciardi

et al. 2020

Sensors

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This paper presents a new wearable e-textile based system, named SWEET Sock, for biomedical signals remote monitoring. The system includes a textile sensing sock, an electronic unit for data transmission, a custom-made Android application for real-time signal visualization, and a software desktop for advanced digital signal processing. The device allows the acquisition of angular velocities of the lower limbs and plantar pressure signals, which are postprocessed to have a complete and schematic overview of patient’s clinical status, regarding gait and postural assessment. In this work, device performances are validated by evaluating the agreement between the prototype and an optoelectronic system for gait analysis on a set of free walk acquisitions. Results show good agreement between the systems in the assessment of gait cycle time and cadence, while the presence of systematic and proportional errors are pointed out for swing and stance time parameters. Worse results were obtained in the comparison of spatial metrics. The “wearability” of the system and its comfortable use make it suitable to be used in domestic environment for the continuous remote health monitoring of de-hospitalized patients but also in the ergonomic assessment of health workers, thanks to its low invasiveness.

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A real time study of the human equilibrium using an instrumented insole with 3 pressure sensors

Cited by 7 publications

References 13 publications

Insole Systems for Disease Diagnosis and Rehabilitation

Insole Systems for Disease Diagnosis and Rehabilitation

Empirical Study on Human Movement Classification Using Insole Footwear Sensor System and Machine Learning

Design and Validation of an E-Textile-Based Wearable Sock for Remote Gait and Postural Assessment

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