Literature DB >> 24110762

Comparing "pick and place" task in spatial Augmented Reality versus non-immersive Virtual Reality for rehabilitation setting.

Maryam Khademi, Hossein Mousavi Hondori, Lucy Dodakian, Steve Cramer, Cristina V Lopes.   

Abstract

Introducing computer games to the rehabilitation market led to development of numerous Virtual Reality (VR) training applications. Although VR has provided tremendous benefit to the patients and caregivers, it has inherent limitations, some of which might be solved by replacing it with Augmented Reality (AR). The task of pick-and-place, which is part of many activities of daily living (ADL's), is one of the major affected functions stroke patients mainly expect to recover. We developed an exercise consisting of moving an object between various points, following a flash light that indicates the next target. The results show superior performance of subjects in spatial AR versus non-immersive VR setting. This could be due to the extraneous hand-eye coordination which exists in VR whereas it is eliminated in spatial AR.

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Year:  2013        PMID: 24110762     DOI: 10.1109/EMBC.2013.6610575

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

Review 1.  Augmented Reality: A Brand New Challenge for the Assessment and Treatment of Psychological Disorders.

Authors:  Irene Alice Chicchi Giglioli; Federica Pallavicini; Elisa Pedroli; Silvia Serino; Giuseppe Riva
Journal:  Comput Math Methods Med       Date:  2015-08-03       Impact factor: 2.238

Review 2.  A Review on Technical and Clinical Impact of Microsoft Kinect on Physical Therapy and Rehabilitation.

Authors:  Hossein Mousavi Hondori; Maryam Khademi
Journal:  J Med Eng       Date:  2014-12-10

3.  A Virtual Versus an Augmented Reality Cooking Task Based-Tools: A Behavioral and Physiological Study on the Assessment of Executive Functions.

Authors:  Irene Alice Chicchi Giglioli; Cristina Bermejo Vidal; Mariano Alcañiz Raya
Journal:  Front Psychol       Date:  2019-11-14

4.  An sEMG-Controlled 3D Game for Rehabilitation Therapies: Real-Time Time Hand Gesture Recognition Using Deep Learning Techniques.

Authors:  Nadia Nasri; Sergio Orts-Escolano; Miguel Cazorla
Journal:  Sensors (Basel)       Date:  2020-11-12       Impact factor: 3.576

  4 in total

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