Literature DB >> 24835230

Exploiting wearable goniometer technology for motion sensing gloves.

Nicola Carbonaro, Gabriele Dalle Mura, Federico Lorussi, Rita Paradiso, Danilo De Rossi, Alessandro Tognetti.   

Abstract

This paper presents an innovative wearable kinesthetic glove realized with knitted piezoresistive fabric (KPF) sensor technology. The glove is conceived to capture hand movement and gesture by using KPF in a double-layer configuration working as angular sensors (electrogoniometers). The sensing glove prototype is endowed by three KPF goniometers, used to track flexion and extension movement of metacarpophalangeal joint of thumb, index, and middle fingers. The glove is devoted to the continuous monitoring of patients during their daily-life activities, in particular for stroke survivors during their rehabilitation. The prototype performances have been evaluated in comparison with an optical tracking system considered as a gold standard both for relieving static and dynamic posture and gesture of the hand. The introduced prototype has shown very interesting figures of merit. The angular error, evaluated through the standard Bland Altman analysis, has been estimated in ±3° which is slightly less accurate than commercial electrogoniometers. Moreover, a new conceptual prototype design, preliminary evaluated within this study, is presented and discussed in order to solve actual limitations in terms of number and type of sensor connections, avoiding mechanical constraints given by metallic inextensible wires and improving user comfort.

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Year:  2014        PMID: 24835230     DOI: 10.1109/JBHI.2014.2324293

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  14 in total

1.  Continuous quantitative monitoring of physical activity in Parkinson's disease patients by using wearable devices: a case-control study.

Authors:  Guoen Cai; Yujie Huang; Shan Luo; Zhirong Lin; Houde Dai; Qinyong Ye
Journal:  Neurol Sci       Date:  2017-06-28       Impact factor: 3.307

2.  A bi-articular model for scapular-humeral rhythm reconstruction through data from wearable sensors.

Authors:  Federico Lorussi; Nicola Carbonaro; Danilo De Rossi; Alessandro Tognetti
Journal:  J Neuroeng Rehabil       Date:  2016-04-23       Impact factor: 4.262

Review 3.  A review of e-textiles in neurological rehabilitation: How close are we?

Authors:  Ruth McLaren; Frances Joseph; Craig Baguley; Denise Taylor
Journal:  J Neuroeng Rehabil       Date:  2016-06-21       Impact factor: 4.262

4.  A Synergy-Based Optimally Designed Sensing Glove for Functional Grasp Recognition.

Authors:  Simone Ciotti; Edoardo Battaglia; Nicola Carbonaro; Antonio Bicchi; Alessandro Tognetti; Matteo Bianchi
Journal:  Sensors (Basel)       Date:  2016-06-02       Impact factor: 3.576

5.  How Therapists Use Visualizations of Upper Limb Movement Information From Stroke Patients: A Qualitative Study With Simulated Information.

Authors:  Bernd Ploderer; Justin Fong; Marlena Klaic; Siddharth Nair; Frank Vetere; L Eduardo Cofré Lizama; Mary Pauline Galea
Journal:  JMIR Rehabil Assist Technol       Date:  2016-10-05

6.  A novel upper-limb function measure derived from finger-worn sensor data collected in a free-living setting.

Authors:  Sunghoon Ivan Lee; Xin Liu; Smita Rajan; Nathan Ramasarma; Eun Kyoung Choe; Paolo Bonato
Journal:  PLoS One       Date:  2019-03-20       Impact factor: 3.240

7.  Wearable Textile Platform for Assessing Stroke Patient Treatment in Daily Life Conditions.

Authors:  Federico Lorussi; Nicola Carbonaro; Danilo De Rossi; Rita Paradiso; Peter Veltink; Alessandro Tognetti
Journal:  Front Bioeng Biotechnol       Date:  2016-03-23

8.  Wearable Goniometer and Accelerometer Sensory Fusion for Knee Joint Angle Measurement in Daily Life.

Authors:  Alessandro Tognetti; Federico Lorussi; Nicola Carbonaro; Danilo de Rossi
Journal:  Sensors (Basel)       Date:  2015-11-11       Impact factor: 3.576

9.  Design of an Inertial-Sensor-Based Data Glove for Hand Function Evaluation.

Authors:  Bor-Shing Lin; I-Jung Lee; Shu-Yu Yang; Yi-Chiang Lo; Junghsi Lee; Jean-Lon Chen
Journal:  Sensors (Basel)       Date:  2018-05-13       Impact factor: 3.847

10.  Efficient Multiaxial Shoulder-Motion Tracking Based on Flexible Resistive Sensors Applied to Exosuits.

Authors:  J Luis Samper-Escudero; Aldo F Contreras-González; Manuel Ferre; Miguel A Sánchez-Urán; David Pont-Esteban
Journal:  Soft Robot       Date:  2020-01-06       Impact factor: 8.071

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