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Purpose: To compare heart rate (HR), oxygen consumption (VO2), blood lactate (BL), and ratings of perceived exertion (RPE) during arm cycling with and without a blood flow restriction (BFR). Methods: Twelve healthy males (age: 23.9 ± 3.75 years) completed four, randomized, 15-min arm cycling conditions: high-workload (HW: 60% maximal power output), low-workload (LW: 30% maximal power output), low-workload with BFR (LW-BFR), and BFR with no exercise (BFR-only). In the BFR conditions, cuff pressure to the proximal biceps brachii was set to 70% of occlusion pressure. HR, VO2, and RPE were recorded throughout the exercise, and BL was measured before, immediately after, and five minutes post-exercise. Within-subject repeated-measures ANOVA was used to evaluate condition-by-time interactions. Results: HW elicited the greatest responses in HR (91% of peak; 163.3 ± 15.8 bpm), VO2 (71% of peak; 24.0 ± 3.7 ml kg−1 min−1), BL (7.7 ± 2.5 mmol L−1), and RPE (14 ± 1.7) and was significantly different from the other conditions (p < 0.01). The LW and LW-BFR conditions did not differ from each other in HR, VO2, BL, and RPE mean of conditions: ~ 68%, 41%, 3.5 ± 1.6 mmol L−1, 10.4 ± 1.6, respectively; p > 0.05). During the BFR-only condition, HR increased from baseline by ~ 15% (on average) (p < 0.01) without any changes in VO2, BL, and RPE (p > 0.05). Conclusions: HW arm cycling elicited the largest and most persistent physiological responses compared to LW arm cycling with and without a BFR. As such, practitioners who prescribe arm cycling for their clients should be advised to augment the demands of exercise via increases in exercise intensity (i.e., power output), rather than by adding BFR. [ABSTRACT FROM AUTHOR]

Purpose of Review: Walking impairments are highly prevalent in persons with multiple sclerosis (PwMS) and are associated with reduced quality of life. Walking is traditionally quantified with various measures, including patient self-reports, clinical rating scales, performance measures, and advanced lab-based movement analysis techniques. Yet, the majority of these measures do not fully characterize walking (i.e., gait quality) nor adequately reflect walking in the real world (i.e., community ambulation) and have limited timescale (only measure walking at a single point in time). We discuss the potential of wearable sensors to provide sensitive, objective, and easy-to-use assessment of community ambulation in PwMS. Recent Findings: Wearable technology has the ability to measure all aspects of gait in PwMS yet is under-studied in comparison with other populations (e.g., older adults). Within the studies focusing on PwMS, half that measure pace collected free-living data, while only one study explored gait variability in free-living conditions. No studies explore gait asymmetry or complexity in free-living conditions. Summary: Wearable technology has the ability to provide objective, comprehensive, and sensitive measures of gait in PwMS. Future research should investigate this technology's ability to accurately assess free-living measures of gait quality, specifically gait asymmetry and complexity. [ABSTRACT FROM AUTHOR]