GAVRe²: Towards Data-Driven Upper-Limb Rehabilitation with Adaptive-Feedback Gamification

Abstract

This paper presents Game Adaptive Virtual Reality Rehabilitation (GAVRe 2), a framework to augment upper limb rehabilitation using Virtual Reality (VR) gamification and haptic robotic manipulator feedback. GAVRe 2 integrates independent systems in a modular fashion, connecting patients with therapists remotely to increase patient engagement during rehabilitation. GAVRe 2 exploits VR capabilities to not only increase the productivity of therapists administering rehabilitation, but also to improve rehabilitation mobility for patients. Conventional rehabilitation requires face-to-face physical interactions in a clinical setting which can be inconvenient for patients. The GAVRe 2 approach provides an avenue for rehabilitation in a domestic setting by remotely customizing a routine for the patient. Results are then reported back to therapists for data analysis and future training regime development. GAVRe 2 is evaluated experimentally through a system that integrates a popular VR system, a RGB-D camera, and a collaborative industrial robot, with results indicating potential benefits for long-term rehabilitation and the opportunity for upper limb rehabilitation in a domestic setting.

Heuristic Detection of Recovery Progress using Robotic Data

“…This paper models the scenario described in [16], targeting the data center. To compare the proposed metric to conventional methods, the collected data sequences are classified into their class-labels and visualized.…”

Robot-Assisted Rehabilitation Architecture Supported by a Distributed Data Acquisition System

“…According to an analysis of the previously mentioned articles, the GUI is implemented in all of the proposed architecture except for [ 18 , 19 , 35 ]; the EMG sensor is not implemented in the majority of the discussed papers [ 18 , 19 , 30 , 31 , 34 , 36 , 37 ]. Furthermore, there is a discrepancy between the rehabilitation strategies, none of the systems presented are able to offer both the possibility to choose between default exercises and the possibility to create exercises and adapt, i.e., either to follow a pre-defined rehabilitation pathway or to create an exercise that the robot will reproduce.…”

Jogos Digitais e Engajamento na Reabilitação de Pacientes: Uma Revisão Sistemática da Literatura

“…Um primeiro pontoé o problema de saúde abordado: tratam-se de disfunções motoras, resultado de grandes períodos de internação, disfunções musculares por Acidentes Vasculares Cerebrais (AVCs), ou ainda pela idade avançada do paciente. Uma grande porção dos artigos dedica-se aos movimentos dos membros superiores (50, 5%) [Lai et al 2018, Pereira et al 2019, Bower et al 2015], enquanto que 9, 6% aos membros inferiores e ainda 39, 7% dos trabalhos, a ambos ou outros tipos de movimentação [Grammatikopoulou et al 2019, Desai et al 2016]. Por essa razão,é unanimidade entre os trabalhos encontrados que o jogo construídoé um exergame, ainda que alguns não sejam formalmente conceituados desta maneira.…”

“…Por outro lado, 46% dos trabalhos (43 artigos) trazem abordagens que utilizam sensores que precisam ser acoplados ao paciente, como goniômetros 9 e equipamentos de Eletroencefalograma (EEG) [Lai et al 2018, Rahman et al 2016]. É vantajosa a precisão dos dados capturados, porém estes equipamentos, além de possuírem alto custo e serem de difícil obtenção, precisam ser vestidos no paciente e configurados adequadamente, o que pode causar desconforto e perda da motivação em realizar a atividade.…”