Bayesian network aided grasp and grip efficiency estimation using a smart data glove for post-stroke diagnosis

• Autorzy: Dutta D. , Modak S. , Kumar A. , Roychowdhury J. , Mandal S.

Identyfikatory

DOI

10.1016/j.bbe.2016.09.005

• Języki publikacji: EN

Abstrakty

EN

Stroke is one of the major causes behind the increased mortality rate throughout the world and disability among the survivors. Such disabilities include several grasp and grip related impairment in daily activities like holding a glass of water, counting currency notes, producing correct signature in bank, etc., that seek serious attention. Present therapeutic facilities, being expensive and time-consuming, fail to cater the poverty stricken rural class of the society. In this paper, on the basis of an investigation, we developed a smart data glove based diagnostic device for better treatment of such patients by providing timely estimation of their grasp quality. Data collected from a VMG30 motion capture glove for six patients who survived stroke and two other healthy subjects was fused with suitable hypothesis obtained from a domain expert to reflect the required outcome on a Bayesian network. The end result could be made available to a doctor at a remote location through a smart phone for further advice or treatment. Results obtained clearly distinguished a patient from a healthy subject along with supporting estimates to study and compare different grasping gestures. The improvement in mobility could be assessed after physiotherapeutic treatments using the proposed method.

Słowa kluczowe

EN

stroke; data glove; Bayesian network; probabilistic estimate; grasping gesture

PL

udar; rękawice danych; sieć Bayesa

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2017
• Tom: Vol. 37, no. 1
• Strony: 44--58
• Opis fizyczny: Bibliogr. 25 poz., rys., tab., wykr.

Twórcy

autor

Dutta D.

• Embedded Systems Laboratory, CSIR-Central Mechanical Engineering Research Institute, Durgapur 713209, West Bengal, India; Academy of Scientific and Innovative Research, India

autor

Modak S.

• Nivedita Health Centre, Durgapur, West Bengal, India

autor

Kumar A.

• Embedded Systems Laboratory, CSIR-Central Mechanical Engineering Research Institute, Durgapur 713209, West Bengal, India

autor

Roychowdhury J.

• Embedded Systems Laboratory, CSIR-Central Mechanical Engineering Research Institute, Durgapur 713209, West Bengal, India; Academy of Scientific and Innovative Research, India

autor

Mandal S.

• Academy of Scientific and Innovative Research, India

Bibliografia

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).