We evaluated the feasibility, safety, and efficacy of a 2D-planar robot for minimally supervised home-based upper-limb therapy for post-stroke hemiparesis. The H-Man, end effector robot, combined with web-based software application for remote tele-monitoring were evaluated at homes of participants. Inclusion criteria were: strokes > 28 days, Fugl-Meyer Motor Assessment (FMA) > 10-60/66, presence of a carer and absence of medical contraindications. Participants performed self-directed, minimally supervised robotics-assisted therapy (RAT) at home for 30 consecutive days, after 2 therapist-supervised clinic on-boarding sessions. Web-based compliance measures were: accessed sessions of > 20 min/day, training minutes/day and active training hours/30 days. Clinical outcomes at weeks 0, 5 (post-training), 12 and 24 (follow-up) consisted of FMA, Action Research Arm Test (ARAT) and WHO-Stroke Specific Quality of Life (SSQOL). To estimate immediate economic benefits of the home-based robotic therapy, we performed cost-effectiveness analysis (CEA), followed by budget impact analysis (BIA). Altogether, all 12 participants completed Home-RAT without adverse events; 9 (75.0%) were males, mean (SD) age, 59.4 years (9.5), median (IQR) stroke duration 38.6 weeks (25.4, 79.6) baseline FMA (0–66) 42.1 ± 13.2, ARAT (0–57) 25.4 ± 19.5, SSQOL (0–245) 185.3 ± 32.8. At week 5 follow-up, mean (SD) accessed days were 26.3 days ± 6.4, active training hours of 35.3 h ± 14.7/30 days, or ~ 6 days/week and 77 training minutes ± 20.9/day were observed. Significant gains were observed from baseline across time; ΔFMA 2.4 at week 5 (FMA 44.5, CI 95% 39.7–49.3, p < 0.05) and ΔFMA 3.7 at week 24 (FMA 45.8, CI 95% 40.5–51, p < 0.05); ΔARAT 2.6 at week 5 (ARAT 28.0, CI 95% 19.3–36.7, p < 0.05), and ΔARAT 4.8 at week 24 (ARAT 30.2, CI 95% 21.2–39.1, p < 0.05). At week 5 follow-up, 91% of participants rated their overall experience as satisfied or very satisfied. Incremental CEA observed savings of -S$144/per cure over 24 weeks, BIA—potentially 12% impact reduction over five years. This study demonstrates the feasibility, acceptability, safety, clinical efficacy, and cost-effectiveness of a home-based, web-enabled telemonitored carer-supervised robotics-aided therapy. Trial registration: NCT05212181 ( https://clinicaltrials.gov ).

Objective: The aim of the study was to pilot the use of Montreal Cognitive Assessment as a quick clinical screen for cognitive assessment in traumatic brain injury patients. Design: The study recruited 61 participants with moderate to severe traumatic brain injury presenting to a tertiary rehabilitation center under the Brain Injury Program. A Montreal Cognitive Assessment questionnaire and neuropsychological battery (Repeatable Battery for the Assessment of Neuropsychological Status and Color Trails Test) were administered to participants who had completed inpatient rehabilitation. Results: Receiver operating characteristic analysis for the Montreal Cognitive Assessment revealed an optimal balance of sensitivity and specificity at 24/25 to discriminate participants who were classified as less than 5th centile on the Total Scale Index on the Repeatable Battery for the Assessment of Neuropsychological Status. This achieved a sensitivity, specificity, PPV, and NPV of 73.9%, 86.5%, 77.3%, and 84.2%, respectively. Receiver operating characteristic analysis for the trail making subtest of the Montreal Cognitive Assessment achieved a sensitivity, specificity, PPV, and NPV of 79.4%, 74.1%, 79.4%, and 74.1% in identifying patients classified as less than 5th centile on Color Trail Test part 2. Conclusions: The use of Montreal Cognitive Assessment displayed good validity in identifying patients with clinically significant impairment on a standard neuropsychological assessment battery in the study population. However, it may lack sensitivity for estimating mild levels of impairment.

Background:COVID-19 (Coronavirus Disease 2019) is a global cause of morbidity and mortality currently. We aim to describe the acute functional outcomes of critically ill coronavirus disease 2019 (COVID-19) patients after transferring out of the intensive care unit (ICU).Methods:51 consecutive critically ill COVID-19 patients at a national designated center for COVID-19 were included in this exploratory, retrospective observational cohort study from January 1 to May 31, 2020. Demographic and clinical data were collected and analyzed. Functional outcomes were measured primarily with the Functional Ambulation Category (FAC), and divided into 2 categories: dependent ambulators (FAC 0–3) and independent ambulators (FAC 4–5). Multivariate analysis was performed to determine associations.Results:Many patients were dependent ambulators (47.1%) upon transferring out of ICU, although 92.2% regained independent ambulation at discharge. On multivariate analysis, we found that a Charlson Comorbidity Index of 1 or more (odds ratio 14.02, 95% CI 1.15–171.28,P= 0.039) and a longer length of ICU stay (odds ratio 1.50, 95% CI 1.04–2.16,P= 0.029) were associated with dependent ambulation upon discharge from ICU.Conclusions:Critically ill COVID-19 survivors have a high level of impairment following discharge from ICU. Such patients should be screened for impairment and managed appropriately by rehabilitation professionals, so as to achieve good functional outcomes on discharge.

SPM is a statistical method of analysis of time-varying human movement gait signal, depending on the random field theory (RFT). MovementRx is our inhouse-developed decision-support system that depends on SPM1D Python implementation of the SPM (spm1d.org). We present the potential application of MovementRx in the prediction of increased joint forces with the possibility to predispose to osteoarthritis in a sample of post-surgical Transtibial Amputation (TTA) patients who were ambulant in the community. We captured the three-dimensional movement profile of 12 males with TTA and studied them using MovementRx, employing the SPM1D Python library to quantify the deviation(s) they have from our corresponding reference data, using “Hotelling 2” and “T test 2” statistics for the 3D movement vectors of the 3 main lower limb joints (hip, knee, and ankle) and their nine respective components (3 joints × 3 dimensions), respectively. MovementRx results visually demonstrated a clear distinction in the biomechanical recordings between TTA patients and a reference set of normal people (ABILITY data project), and variability within the TTA patients’ group enabled identification of those with an increased risk of developing osteoarthritis in the future. We conclude that MovementRx is a potential tool to detect increased specific joint forces with the ability to identify TTA survivors who may be at risk for osteoarthritis.