SQUID: Sensorized shirt with smartphone interface for exercise monitoring and home rehabilitation

Farjadian, Amir B.; Sivak, Mark; Mavroidis, Constantinos

doi:10.1109/icorr.2013.6650451

Cited by 14 publications

(6 citation statements)

References 18 publications

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“…In 2013, a different sensorized shirt was presented by Farjadian et al [ 130 ], named SQUID. This prototype was developed with the aim of home rehabilitation to monitor and evaluate physical therapy exercise with an online database for therapists’ remote supervision from a hospital.…”

Section: Wearable Health Devices—systemsmentioning

confidence: 99%

Wearable Health Devices—Vital Sign Monitoring, Systems and Technologies

Dias

Cunha

2018

Sensors

675

361

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Wearable Health Devices (WHDs) are increasingly helping people to better monitor their health status both at an activity/fitness level for self-health tracking and at a medical level providing more data to clinicians with a potential for earlier diagnostic and guidance of treatment. The technology revolution in the miniaturization of electronic devices is enabling to design more reliable and adaptable wearables, contributing for a world-wide change in the health monitoring approach. In this paper we review important aspects in the WHDs area, listing the state-of-the-art of wearable vital signs sensing technologies plus their system architectures and specifications. A focus on vital signs acquired by WHDs is made: first a discussion about the most important vital signs for health assessment using WHDs is presented and then for each vital sign a description is made concerning its origin and effect on heath, monitoring needs, acquisition methods and WHDs and recent scientific developments on the area (electrocardiogram, heart rate, blood pressure, respiration rate, blood oxygen saturation, blood glucose, skin perspiration, capnography, body temperature, motion evaluation, cardiac implantable devices and ambient parameters). A general WHDs system architecture is presented based on the state-of-the-art. After a global review of WHDs, we zoom in into cardiovascular WHDs, analysing commercial devices and their applicability versus quality, extending this subject to smart t-shirts for medical purposes. Furthermore we present a resumed evolution of these devices based on the prototypes developed along the years. Finally we discuss likely market trends and future challenges for the emerging WHDs area.

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Section: Wearable Health Devices—systemsmentioning

confidence: 99%

Wearable Health Devices—Vital Sign Monitoring, Systems and Technologies

Dias

Cunha

2018

Sensors

675

361

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“…However, it does not examine the muscle activity of the user. Garment in [31] use electromyography (EMG) to detect muscle activity and assist the user in physical therapy. There are few proposed solutions that use accelerometer data to analyze the intensity of exercises, however, it cannot be used in calculating individual muscle activity in comparison to using sEMG.…”

Section: Related Prior Researchmentioning

confidence: 99%

MyWear: A Smart Wear for Continuous Body Vital Monitoring and Emergency Alert

Sethuraman¹,

Kompally²,

Mohanty³

et al. 2020

Preprint

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Smart healthcare which is built as healthcare Cyber-Physical System (H-CPS) from Internet-of-Medical-Things (IoMT) is becoming more important than before. Medical devices and their connectivity through Internet with alongwith the electronics health record (EHR) and AI analytics making H-CPS possible. IoMT-end devices like wearables and implantables are key for H-CPS based smart healthcare. Smart garment is a specific wearable which can be used for smart healthcare. There are various smart garments that help users to monitor their body vitals in real-time. Many commercially available garments collect the vital data and transmit it to the mobile application for visualization. However, these don't perform real-time analysis for the user to comprehend their health conditions. Also, such garments are not included with an alert system to alert users and contacts in case of emergency. In MyWear, we propose a wearable body vital monitoring garment that captures physiological data and automatically analyses such heart rate, stress level, muscle activity to detect abnormalities. A copy of the physiological data is transmitted to the cloud for detecting any abnormalities in heart beats and predict any potential heart failure in future. We also propose a deep neural network (DNN) model that automatically classifies abnormal heart beat and potential heart failure. For immediate assistance in such a situation, we propose an alert system that sends an alert message to nearby medical officials. The proposed MyWear has an average accuracy of 96.9% and precision of 97.3% for detection of the abnormalities.

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“…As a way of simplifying the overall setup and complexity of the procedures involved in EMG biofeedback, Farjadian, Sivak and Mavroidis, [15] proposed a t-shirt that acquires multiple EMG channels and heart rate data. A smartphone interface provides audiovisual feedback, enabling the user to observe and adjust the exercises in real time.…”

Section: Audiovisual Biofeedbackmentioning

confidence: 99%

A Context-Aware Application to Increase Elderly Users Compliance with Physical Rehabilitation Exercises at Home via Animatronic Biofeedback

et al. 2015

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This version is available at https://strathprints.strath.ac.uk/54353/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. Abstract Biofeedback from physical rehabilitation exercises has proved to lead to faster recovery, better outcomes, and increased patient motivation. In addition, it allows the physical rehabilitation processes carried out at the clinic to be complemented with exercises performed at home. However, currently existing approaches rely mostly on audio and visual reinforcement cues, usually presented to the user on a computer screen or a mobile phone interface. Some users, such as elderly people, can experience difficulties to use and understand these interfaces, leading to non-compliance with the rehabilitation exercises. To overcome this barrier, latest biosignal technologies can be used to enhance the efficacy of the biofeedback, decreasing the complexity of the user interface. In this paper we propose and validate a contextaware framework for the use of animatronic biofeedback, as a way of potentially increasing the compliance of elderly users with physical rehabilitation exercises performed at home. in the scope of our work, animatronic biofeedback entails the use of pre-programmed actions on a robot that are triggered in response to certain changes detected in the users' biomechanical or electrophysiological signals. We use electromyographic and accelerometer signals, collected in real time, to monitor the performance of the user while execut- ing the exercises, and a mobile robot to provide animatronic reinforcement cues associated with their correct or incorrect execution. A context-aware application running on a smartphone aggregates the sensor data and controls the animatronic feedback. The acceptability of the animatronic biofeedback has been tested on a set of volunteer elderly users. The results suggest that the participants found the animatronic feedback engaging and of added value.

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SQUID: Sensorized shirt with smartphone interface for exercise monitoring and home rehabilitation

Cited by 14 publications

References 18 publications

Wearable Health Devices—Vital Sign Monitoring, Systems and Technologies

Wearable Health Devices—Vital Sign Monitoring, Systems and Technologies

MyWear: A Smart Wear for Continuous Body Vital Monitoring and Emergency Alert

A Context-Aware Application to Increase Elderly Users Compliance with Physical Rehabilitation Exercises at Home via Animatronic Biofeedback

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