Piezoelectric-Based Insole Force Sensing for Gait Analysis in the Internet of Health Things

Gao, Shuo; Chen, Junliang; Dai, Yanning; Wang, Rui; Kang, Shuaibo; Xu, Lijun

doi:10.1109/mce.2020.2986828

Cited by 21 publications

(27 citation statements)

References 15 publications

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“…Drawbacks of adhesive insole systems, like sensors overlap, friction and unstable mechanical capacity, can be addressed by Fig. 2 (a) structure of piezoelectric insole systems [130]; (b) piezoelectric prototypes [129]; (c) structure of capacitive insole systems [131]; (d) prototypes of capacitive insole systems [128] whole-piece design and fabrication, which are based on screen printing technology. Therefore, some commercialized products like the F-scan® system [15], which has a sensing pressure in the range of 7 kpa to 1043 kpa; the multiwalled carbon nanotube -polydimethylsiloxane based sensors array [16], and the SurroSense Rx Insole produced by company Orpyx SI are widely utilized.…”

Section: A Piezoresistive Techniquesmentioning

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.

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Section: A Piezoresistive Techniquesmentioning

confidence: 99%

Insole Systems for Disease Diagnosis and Rehabilitation

Gao¹,

Zhang²,

Wang³

et al. 2022

Preprint

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“…A wide range of touch screen (such as 5-Wire Resistive, Surface Capacitive touch, Projected Capacitive (P-Cap), Surface Acoustic Wave (SAW) and Infrared (IR) [170]) sensors are available in the market that can be selected for ATMs, kiosks, vending machines, smart devices or wearables' screens. High-performance piezoresistivity, capacitance or piezoelectric pressure sensors can be miniaturized using silicon fabrication techniques, for example piezoelectric based insole sensor [171]. Time-of-Flight 3D sensors utilise Light Detection and Ranging (LIDAR) to measure distances and sizes, to track motions, and to convert the shape of objects into 3D models [172,173].…”

Section: Prospects and Opportunitiesmentioning

confidence: 99%

A Survey of Human-Computer Interaction (HCI) & Natural Habits-based Behavioral Biometric Modalities for User Recognition Schemes

Gupta¹,

Maple²,

Crispo³

et al. 2022

Preprint

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The proliferation of Internet of Things (IoT) systems is having a profound impact across all aspects of life. Recognising and identifying particular users is central to delivering the personalised experience that citizens want to experience, and that organisations wish to deliver. This article presents a survey of human-computer interaction-based (HCI-based) and natural habits-based behavioral biometrics that can be acquired unobtrusively through smart devices or IoT sensors for user recognition purposes. Robust and usable user recognition is also a security requirement for emerging IoT ecosystems to protect them from adversaries. Typically, it can be specified as a fundamental building block for most types of human-to-things accountability principles and access-control methods. However, end-users are facing numerous security and usability challenges in using currently available knowledge- and token-based recognition (i.e., authentication and identification) schemes. To address the limitations of conventional recognition schemes, biometrics, naturally come as a first choice to supporting sophisticated user recognition solutions. We perform a comprehensive review of touch-stroke, swipe, touch signature, hand-movements, voice, gait and footstep behavioral biometrics modalities. This survey analyzes the recent state-of-the-art research of these behavioral biometrics with a goal to identify their attributes and features for generating unique identification signatures. Finally, we present security, privacy, and usability evaluations that can strengthen the designing of robust and usable user recognition schemes for IoT applications.

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“…With the analysis of the human walking process and the results of existing research work, we summarize the basic requirements for materials and device architectures used in plantar pressure detection as follows [ 15–19 ] : 1) mechanical properties: flexible material rather than brittle material is suitable for frequent bending during walking; 2) full sensing scale: the upper limit of normal stress range is widely agreed to be over 1000 kPa in walking analysis, 1900 kPa in daily activities, and 3000 kPa in some extreme situations [ 15,16 ] ; 3) pressure resolution: <10 kPa is a widely accepted index for insole applications (e.g., abnormal pattern detection for PD) based on plantar pressure sensors [ 17 ] ; For detecting the pressure abnormality in associated regions of some specific diseases (e.g., diabetes, rheumatoid arthritis (RA), flat foot and cavus foot), the pressure resolution should be <1 kPa; 4) pressure detection error: less than 1% full scale; 5) measurement bandwidth: 100 Hz for walking, and 200 Hz for vigorous exercises (e.g., running and jumping); 6) compatibility for both static measurement and dynamic measurement; 7) hysteresis: less than 5% full scale; 8) stability: error < 5% full scale for each sensor after more than ten thousands loading‐unloading cycles; 9) shear pressure detection is expected for some specific diseases, such as patients with diabetes. [ 19 ]…”

Section: Insole Pressure Sensor Constructionsmentioning

confidence: 99%

“…Through the appropriate selection of R f and C f to set the desired cut‐off frequency for insole plantar pressure detection, [ 130 ] this method can detect plantar pressure with high accuracy and stability. [ 19,48 ]…”

Section: The Electronics Design For Pressure Sensingmentioning

confidence: 99%

Plantar Pressure‐Based Insole Gait Monitoring Techniques for Diseases Monitoring and Analysis: A Review

Chen

Dai

Grimaldi

et al. 2021

Adv Materials Technologies

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Among diverse wearable techniques, insole‐based plantar pressure monitoring systems have surged as a leading technology to monitor patient's chronic disease progression. Such technological feat has been made possible due to the strong correlation between gait and disease status. Hence, insole‐based plantar pressure monitoring techniques are growing rapidly worldwide; with several research institutions and enterprises showing an increased interest in the field. This review intends to first explain the working principles of mainstream insole plantar sensing techniques and design considerations such as sensing material selection and electronics design requirements, and then the state‐of‐the‐art algorithms for plantar pressure distribution reconstruction. Following, this article will discuss disease monitoring applications and the extraction of disease features. Finally, insight regarding common challenges and their potential solutions within the field would be elucidated.

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Piezoelectric-Based Insole Force Sensing for Gait Analysis in the Internet of Health Things

Cited by 21 publications

References 15 publications

Insole Systems for Disease Diagnosis and Rehabilitation

Insole Systems for Disease Diagnosis and Rehabilitation

A Survey of Human-Computer Interaction (HCI) & Natural Habits-based Behavioral Biometric Modalities for User Recognition Schemes

Plantar Pressure‐Based Insole Gait Monitoring Techniques for Diseases Monitoring and Analysis: A Review

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