PROJECT SUMMARY About 37 million people live with human immunodeficiency virus (HIV) worldwide and about 71% of people living with HIV (PLWH) reside in low and middle income countries (LMICs). HIV enters the central nervous system (CNS) early after infection and increases the risk for mild-to-severe neurocognitive and cardiovascular disorders. Studies show that about 30 to 40% of PLWH will have neurologic complications leading to long-term motor and cognitive disability, including HIV-Associated Neurocognitive Disorders (HAND). Few studies have examined how best to provide objective assessment, diagnostic, and rehabilitative treatment tools to aid people living with disabilities as a result of HIV and HIV-stroke in LMICs. The need for these tools is great in LMICs, given the greatly limited infrastructure and healthcare resources and thus decreased access to consistent, quality rehabilitation. Our long-term goal is to develop innovative and affordable robot technologies to bridge healthcare care gaps in LMICs and leverage them to help objectively assess, diagnose and treat PLWH presenting with motor and cognitive impairment due to HAND and Stroke. In this R21 project, we leverage our affordable robot therapy system augmented with objective metrics and motor and cognitive exergames to assess PLWH in Botswana—a country with the fourth highest HIV prevalence rate (20.3%) in the world, an increasing NCD prevalence rate, and limited rehab resources. Aim 1 determines concurrent validity and reliability of using the robot therapy system to objectively ASSESS cognitive, and motor impairments in PLWH. Forty (40) PLWH and 40 HIV-negative controls will be evaluated using both clinical metrics and new robot-based metrics at two time points, at least 1-week apart. We hypothesize that robot-based metrics will have test-retest reliability as well as concurrent validity with clinical measures of motor and cognitive function that usually require rehabilitation expertise and man-power to complete. Aim 2 determines the feasibility of developing a robot-based classification of HIV-associated neurocognitive disorders (HAND). 80 PLWH without stroke will be evaluated using an augmented neuropsychological (NP) battery required to meet minimal HAND Frascati criteria and the robot assessment tasks. We will use the Frascati criteria and global deficit scoring (GDS) to classify the PLWH participants into asymptomatic neurocognitive impairment (ANI), mild neurocognitive disorder (MND) and HIV- associated dementia (HAD). We will develop a regression model using derived robot metrics and test its ability to predict HAND and GDS score. We hypothesize that the robot-based model will classify HAND with specificity and sensitivity better than HAND screening with International HIV Dementia Scale and Montreal Cognitive Assessment. The Receiver Operator Curve (ROC) will be used as empirical validation. Demographic, HIV, and lifestyle factors such as age, viral load, hypertension, dia...