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Background: This study aimed to identify and quantify the kinematic and kinetic gait deviations in post-stroke hemiplegic patients with matched healthy controls using Statistical Parametric Mapping (SPM). Methods: Fifteen chronic stroke patients [4 females, 11 males; age 53.7 (standard deviation 12.2) years; body mass 65.4 (10.4) kg; standing height 168.5 (9.6) cm] and 15 matched healthy controls [4 females, 11 males; age 52.9 (11.7) years; body weight 66.5 (10.7) years; standing height 168.3 (8.8) cm] were recruited. In a 10-m walking task, joint angles, ground reaction forces (GRF), and joint moments were collected, analyzed, and compared using SPM for an entire gait cycle. Results: Generally, when comparing the stroke patients' affected (hemiplegic) and less-affected (contralateral) limbs with the control group, SPM identified significant differences in the late stance phase and early swing phase in the joint angles and moments in bilateral limbs (all p < 0.005). In addition, the vertical and anteroposterior components of GRF were significantly different in various periods of the stance phase (all p < 0.005), while the mediolateral component showed no differences between the two groups. Conclusion: SPM was able to detect abnormal gait patterns in both the affected and less-affected limbs of stroke patients with significant differences when compared with matched controls. The findings draw attention to significant quantifiable gait deviations in the less-affected post-stroke limb with the potential impact to inform gait retraining strategies for clinicians and physiotherapists. [ABSTRACT FROM AUTHOR]

Introduction: We examined the association between admission body mass index (BMI) and discharge rehabilitation functional outcome using the functional independence measure (FIM) in a Southeast Asian cohort of stroke patients during inpatient rehabilitation. Methods: A prospective, observational cohort study of stroke patients admitted to a single inpatient rehabilitation unit was conducted. Using the World Health Organization Asian standards, BMI was classified as underweight (<18.5 kg/m²), normal (18.5-22.9 kg/m²) and overweight (≥23 kg/m²). The primary outcome measure was discharge FIM, and secondary outcomes included FIM gain, FIM efficiency and FIM effectiveness. Results: Two hundred and forty-seven stroke subjects were enrolled. The mean age of the cohort was 59.48 (standard deviation [SD] 12.35) years; 64.4% (n = 159) were male and 52.6% (n = 130) had ischaemic stroke. The distributions of underweight, normal and overweight based on BMI on admission were 10.9% (n = 27), 33.2% (n = 82) and 55.9% (n = 138), respectively, and the distributions upon discharge were 11.7% (n = 29), 38.1% (n = 94) and 50.2% (n = 124), respectively. Significant small decreases in BMI from admission to discharge were found (median [interquartile range] 23.58 [23.40-24.70] vs. 23.12 [22.99-24.21]; P < 0.001). Similarly, clinically significant FIM gains (mean ΔFIM 26.71; 95% confidence interval 24.73, 28.69, P < 0.001) were noted after a median length of stay of 36 days. No significant relationships were found between BMI and discharge FIM (P = 0.600), FIM gain (P = 0.254), FIM efficiency (P = 0.412) or FIM effectiveness (P = 0.796). Conclusion: Findings from this study unequivocally support the benefits of acute inpatient stroke rehabilitation. Patients in the obese BMI range tended to normalise during rehabilitation. Body mass index, whether underweight, normal or overweight, did not correlate with discharge FIM. [ABSTRACT FROM AUTHOR]

In this article, we discuss robotic-assisted therapy as an emerging and significant field of clinical rehabilitation and its value proposition for innovating rehabilitation clinical practice. Attempts to achieve integration among clinicians' practices and bioengineers' machines often generate new challenges and controversies. To date, the literature is indicative of a sizeable number and variety of robotic devices in the field of clinical rehabilitation, some are commercially available; however, large-scale clinical outcomes are less positive than expected. The following main themes related to integrating rehabilitation technology in real-world clinical practice will be discussed: the application of current evidence-based practice and knowledge in relation to treatment in the rehabilitation clinic, perspectives from rehabilitation professionals using robotic-aided therapy with regard to challenges, and strategies for problem solving. Lastly, we present innovation philosophies with regard to sustainability of clinical rehabilitation technologies. [ABSTRACT FROM AUTHOR]