Stroke is becoming one of the leading causes of adult disability and death in sub-Saharan African countries. The aim of the present study is to provide an up-to-date account of the clinical and demographic characteristics of patients with stroke admitted to the

Stroke is the leading cause of adult disability worldwide, with 70 percent of survivors exhibiting residual impairments of the upper limb that require frequent in-person visits to rehabilitation clinic over several months. This study explored rehabilitation clinician's preferences for design features to be included in an mHealth-enabled app for post-stroke upper limb rehabilitation. Data were collected via online survey, sampling participants from Ethiopia (n = 69) and the United States (n = 75). Survey results indicated that Ethiopian and US rehabilitation clinicians have different opinions about the importance of design features that should be included in a stroke tele-rehabilitation system which are likely due to differences in culture, the availability of human and physical resources, and how the field of rehabilitation is organized and managed. Our results, thus, indicate that mHealth technologies must be tailored to the geographical and cultural context of the end users.

The development of context-appropriate sensor technologies could alleviate the significant burden of stroke in Sub-Saharan African rehabilitation clinicians and health care facilities. However, many commercially available wearable sensors are beyond the financial capabilities of the majority of African persons. In this study, we evaluated the concurrent validity of a low-cost wearable sensor (i.e., the outREACH sensor) to measure upper limb movement kinematics of 31 healthy persons, using an 8-camera Vicon motion capture system as the reference standard. The outREACH sensor showed high correlation (r range: 0.808–0.990) and agreement (mean difference range: −1.60 to 1.10) with the reference system regardless of task or kinematic parameter. Moreover, Bland-Altman analyses indicated that there were no significant systematic errors present. This study indicates that upper limb movement kinematics can be accurately measured using the outREACH sensor, and have the potential to enhance stroke evaluation and rehabilitation in sub-Saharan Africa.

Acquired brain injuries place a significant burden on sub-Saharan African rehabilitation clinicians and health care facilities. While wearable sensors have the potential to alleviate these issues, many are beyond the financial capabilities of the majority of African persons and clinics. To bridge this gap, we have developed a low-cost wrist-worn sensor (the outREACH sensor) capable of accurately measuring upper limb movement kinematics. In this study we evaluated the extent to which the outREACH sensor is sensitive to the hand performing the task (unimpaired, impaired) and level of impairment (mild, moderate) in 14 Ethiopian persons with acquired brain injury (mean age = 51.6 ± 12.2 years, 1 female, 13 male). Participants performed an object manipulation task with both the impaired and the unimpaired limb, and reaching performance was measured using standard kinematic measures (i.e., movement time, spectral arc length, peak velocity, peak acceleration, mean velocity, mean acceleration). Overall, movements were smoother and faster when performed by the patient's unimpaired limb. In contrast, maximum velocity did not differ between the two limbs. Moreover, the outREACH sensor was sensitive to differences in performance-based upper limb impairment. Fugl-Meyer assessment for upper extremity scores were significantly correlated with movement time, spectral arc length, and peak velocity. Upper limb movement kinematics can be accurately measured using the outREACH sensor. The outREACH sensor can be a valuable addition to standardized clinical measures that provides rehabilitation clinicians with information regarding initial upper limb impairment level and changes in function across the rehabilitation lifespan.

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UNSTRUCTURED Stroke is the leading cause of adult disability worldwide, with 70% of survivors exhibiting residual impairments of the upper limb that require frequent in-person visits to rehabilitation clinic over several months. This study explored rehabilitation clinician’s preferences for design features to be included in an mHealth-enabled app for post-stroke upper-limb rehabilitation. Data were collected via online survey, sampling participants from Ethiopia (n = 37) and the U.S. (n = 40). Survey results indicated that Ethiopian and U.S. rehabilitation clinicians have different opinions about the importance of design features that should be included in a stroke tele-rehabilitation system which are likely due to differences in culture, the availability of human and physical resources, and how the field of rehabilitation is organized and managed. Our results, thus, indicate that mHealth technologies but must be tailored to the geographical and cultural context of the end-users.