Combined psychophysical and neurophysiological studies have shown that the perceived roughness of surfaces with element spacings of >1 mm is based on spatial variation in the firing rates of slowly adapting type 1 (SA1) afferents (mean absolute difference in firing rates between SA1 afferents with receptive fields separated by approximately 2 mm). The question addressed here is whether this mechanism accounts for the perceived roughness of surfaces with element spacings of <1 mm. Twenty triangular and trapezoidal gratings plus a smooth surface were used as stimulus patterns [spatial periods, 0.1-2.0 mm; groove widths (GWs), 0.1-2.0 mm; and ridge widths (RWs), 0-1.0 mm]. In the human psychophysical studies, we found that the following equation described the mean roughness magnitude estimates of the subjects accurately (0.99 correlation): 0.2 + 1.6GW - 0.5RW - 0.25GW(2). In the neurophysiological studies, these surfaces were scanned across the receptive fields of SA1, rapidly adapting, and Pacinian (PC) afferents, innervating the glabrous skin of anesthetized macaque monkeys. SA1 spatial variation was highly correlated (0.97) with human roughness judgments. There was no consistent relationship between PC responses and roughness judgments; PC afferents responded strongly and almost equally to all of the patterns. Spatial variation in SA1 firing rates is the only neural code that accounts for the perceived roughness of surfaces with finely and coarsely spaced elements. When surface elements are widely spaced, the spatial variation in firing rates is determined primarily by the surface pattern; when the elements are finely spaced, the variation in firing rates between SA1 afferents is determined by stochastic variation in spike rates.

Mobile health tools that enable clinicians and researchers to monitor the type, quantity, and quality of everyday activities of patients and trial participants have long been needed to improve daily care, design more clinically meaningful randomized trials of interventions, and establish cost-effective, evidence-based practices. Inexpensive, unobtrusive wireless sensors, including accelerometers, gyroscopes, and pressure-sensitive textiles, combined with Internet-based communications and machine-learning algorithms trained to recognize upper- and lower-extremity movements, have begun to fulfill this need. Continuous data from ankle triaxial accelerometers, for example, can be transmitted from the home and community via WiFi or a smartphone to a remote data analysis server. Reports can include the walking speed and duration of every bout of ambulation, spatiotemporal symmetries between the legs, and the type, duration, and energy used during exercise. For daily care, this readily accessible flow of real-world information allows clinicians to monitor the amount and quality of exercise for risk factor management and compliance in the practice of skills. Feedback may motivate better self-management as well as serve home-based rehabilitation efforts. Monitoring patients with chronic diseases and after hospitalization or the start of new medications for a decline in daily activity may help detect medical complications before rehospitalization becomes necessary. For clinical trials, repeated laboratory-quality assessments of key activities in the community, rather than by clinic testing, self-report, and ordinal scales, may reduce the cost and burden of travel, improve recruitment and retention, and capture more reliable, valid, and responsive ratio-scaled outcome measures that are not mere surrogates for changes in daily impairment, disability, and functioning.

Neurologic rehabilitation aims to reduce impairments and disabilities so that persons with serious stroke can return to participation in usual self-care and daily activities as independently as feasible. New strategies to enhance recovery draw from a growing understanding of how types of training, progressive task-related practice of skills, exercise for strengthening and fitness, neurostimulation, and drug and biological manipulations can induce adaptations at multiple levels of the nervous system. Recent clinical trials provide evidence for a range of new interventions to manage walking, reach and grasp, aphasia, visual field loss, and hemi-inattention.

Background Walking-related disability is the most frequent reason for inpatient stroke rehabilitation. Task-related practice is a critical component for improving patient outcomes. Objective To test the feasibility of providing quantitative feedback about daily walking performance and motivating greater skills practice via remote sensing. Methods In this phase III randomized, single blind clinical trial, patients participated in conventional therapies while wearing wireless sensors (tri-axial accelerometers) at both ankles. Activity-recognition algorithms calculated the speed, distance, and duration of walking bouts. Three times a week, therapists provided either feedback about performance on a 10-meter walk (speed-only) or walking speed feedback plus a review of walking activity recorded by the sensors (augmented). Primary outcomes at discharge included total daily walking time, derived from the sensors, and a timed 15-meter walk. Results Sixteen rehabilitation centers in 11 countries enrolled 135 participants over 15 months. Sensors recorded more than 1800 days of therapy, 37,000 individual walking bouts, and 2.5 million steps. No significant differences were found between the two feedback groups in daily walking time (15.1±13.1min vs. 16.6±14.3min, p=0.54) or 15-meter walking speed (0.93±0.47m/s vs. 0.91±0.53m/s, p=0.96). Remarkably, 30% of participants decreased their total daily walking time over their rehabilitation stay. Conclusions In this first trial of remote monitoring of inpatient stroke rehabilitation, augmented feedback beyond speed alone did not increase the time spent practicing or improve walking outcomes. Remarkably modest time was spent walking. Wireless sensing, however, allowed clinicians to audit skills practice and provided ground truth regarding changes in clinically important, mobility-related activities.