Quantitative Frailty Assessment Based on Kinematic Parameters of Daily Living Activities.

Frailty is a prevailing phenomena in older people. It is an age related syndrome that can increase the risk of fall in elderly. The people with age above 65 suffers from various functional decline and cognitive impairments.

Patient-Specific Robot-Assisted Stroke Rehabilitation Guided by EEG - A Feasibility Study.

Multi-session robot-assisted stroke rehabilitation program requires patients to perform repetitive tasks. It is challenging for the patient to maintain concentration during training sessions. A novel intervention strategy using Electroencephalography (EEG) signals is proposed to maintain concentration during training by enhancing the engagement of stroke patients using robot-assisted multi-session rehabilitation.

Assessment of frailty: a survey of quantitative and clinical methods.

Background: Frailty assessment is a critical approach in assessing the health status of older people. The clinical tools deployed by geriatricians to assess frailty can be grouped into two categories; using a questionnaire-based method or analyzing the physical performance of the subject. In performance analysis, the time taken by a subject to complete a physical task such as walking over a specific distance, typically three meters, is measured.

Body postural sway analysis in older people with different fall histories.

A cross-sectional study of postural sway analysis in older non-fallers, once-fallers and multiple-fallers using five common standing tests was conducted. Eighty-six older subjects with an average age of 80.4 years (SD ± 7.

The Combined Effects of Adaptive Control and Virtual Reality on Robot-Assisted Fine Hand Motion Rehabilitation in Chronic Stroke Patients: A Case Study.

Robot-assisted therapy is regarded as an effective and reliable method for the delivery of highly repetitive training that is needed to trigger neuroplasticity following a stroke. However, the lack of fully adaptive assist-as-needed control of the robotic devices and an inadequate immersive virtual environment that can promote active participation during training are obstacles hindering the achievement of better training results with fewer training sessions required. This study thus focuses on these research gaps by combining these 2 key components into a rehabilitation system, with special attention on the rehabilitation of fine hand motion skills.

Clinical effectiveness of combined virtual reality and robot assisted fine hand motion rehabilitation in subacute stroke patients.

Robot-assisted therapy is regarded as an effective and reliable method for the delivery of highly repetitive rehabilitation training in restoring motor skills after a stroke. This study focuses on the rehabilitation of fine hand motion skills due to their vital role in performing delicate activities of daily living (ADL) tasks. The proposed rehabilitation system combines an adaptive assist-as-needed (AAN) control algorithm and a Virtual Reality (VR) based rehabilitation gaming system (RGS).