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nº | Title | Author | Evaluation Type | Evaluation Approach | Method used | Subjects | Body part and Movements used to control application | Type of pathologies | QualSyst Quantitative |
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17 | Functional gait rehabilitation in elderly people following a fall-related hip fracture using a treadmill with visual context: design of a randomized controlled trial. | MW, van Ooijen | task performance | objective measures | performance analysis | Estimated: 126 older adults | walking ability and reducing fall incidence | injuries | 74.04% |
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18 | A Kinect-Based System for Lower Limb Rehabilitation in Parkinson’s Disease Patients: a Pilot Study | Palacios-Navarro, Guillermo | task performance | objective measures | task execution, performance analysis | (A) 7 healthy subjects; (B) 7 patients | Lower Limb; lateral leg movements | Parkinson’s Disease Patients with idiopathic | 67.42% |
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19 | SleeveAR: Augmented reality for rehabilitation using real-time feedback | Sousa, M et al | task performance, perception and cognition | objective and subjective measures, informal evaluations | task execution, performance analysis, questionnaire, interview | 18: 14 male and 4 female. Average 26 years old | Upper arm and forearm | injuries | 66.67% |
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20 | Visually-guided gait training in paretic patients during the first rehabilitation phase: study protocol for a randomized controlled trial | Rossano, Cathia | task performance | objective measures | performance analysis | The current estimation is that a total of 70 to 100 participants will be recruited. | Human walking; the muscles of the lower limbs | Stroke | 66.67% |
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21 | An augmented reality home-training system based on the mirror training and imagery approach | Trojan, Jörg | task performance | objective measures | task execution, performance analysis | 7 healthy participants | hand training; treatment for phantom limb pain | Several clinical conditions, such as phantom limb pain, stroke and complex regional pain syndrome. | 63.64% |
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22 | Walking adaptability therapy after stroke: study protocol for a randomized controlled trial | Timmermans, Celine | task performance | objective measures | task execution, performance analysis | 40 persons after stroke (≥3 months) | Human walking; | Stroke | 62.05% |
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23 | Data modeling mobile augmented reality: integrated mind and body rehabilitation | Hsiao, Kuei Fang | UX | subjective measures | questionnaire, interview | 51 senior citizens | Wrist & Arm, Neck and Knee | Alzheimer | 60.42% |
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24 | Augmented reality-based training system for hand rehabilitation | Liu, Jia | task performance | objective and subjective measures | performance analysis, questionnaire | 20 heathy subjects | hand rehabilitation | Stroke | 58.33% |
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25 | Hand tracking and trajectory analysis for physical rehabilitation | Boato, G. | task performance | objective measures | task execution, performance analysis | was not informed | Hand | injuries or cognitive disabilities. | 47.73% |
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26 | Design and Assessment of a Remote Vibrotactile Biofeedback System for Neuromotor Rehabilitation Using Active Markers | Montaño-Murillo, R. | task performance | objective measures | performance analysis | 8 patients | Upper limbs ( shoulders, elbows or wrists) | injuries | 45.08% |
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27 | Evaluation the Post-Stroke Patients Progress Using an Augmented Reality Rehabilitation System | Alamri, Atif | task performance | objective measures | task execution, performance analysis | 15 healthy subjects | Hand, upper limb | Stroke | 43.75% |
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28 | Manipulating the experience of reality for rehabilitation applications | Regenbrecht, Holger | perception and cognition, UX | subjective measures, qualitative analysis, informal evaluations | questionnaire | (A) 24 participants; (B) 30 participants; (C) 43 participants; (D) 2 tests: 23 participants and 30 participants; (E) 100 physiotherapists, who evaluated the system in the role as a therapist and as a patient | Hands and Fingers | Stroke | 43.18% |
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29 | A Gesture Control System to Support Rehabilitation Exercises | Sousa, Kleber A. | task performance | objective measures | task execution, performance analysis | 10 participants (19 to 24 years, 8 men e 2 women) | 15 joints | injuries | 40.91% |
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30 | AR-Rehab: An augmented reality framework for post stroke-patient rehabilitation | Alamri, Atif | task performance | objective and subjective measures | task execution, performance analysis, questionnaire, observation | 15 subjects | poststroke-patient rehabilitation of his / her hands and arms | Stroke | 37.50% |
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31 | Cloud-Based Rehabilitation Exergames System | Hoda, Mohamad | task performance, UX | objective and subjective measures | performance analysis, questionnaire | 6 subjects | upper limb | Stroke | 37.50% |
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32 | Rehabilitation exercise with real-time muscle simulation based EMG and AR | Aung, Yee Mon | task performance | objective measures | questionnaire | 5 healthy subjects | Shoulder | Traumatic Brain Injury (TBI), Spinal Cord Injury (SCI) and Stroke or Cerebrovascular Accident (CVA) | 25.00% |
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