BackgroundVirtual reality (VR)-based rehabilitation has been reported to have beneficial effects on upper extremity function in stroke survivors; however, there is limited information about its effects on distal upper extremity function and health-related quality of life (HRQoL). The purpose of the present study was to examine the effects of VR-based rehabilitation combined with standard occupational therapy on distal upper extremity function and HRQoL, and compare the findings to those of amount-matched conventional rehabilitation in stroke survivors.MethodsThe present study was a single-blinded, randomized controlled trial. The study included 46 stroke survivors who were randomized to a Smart Glove (SG) group or a conventional intervention (CON) group. In both groups, the interventions were targeted to the distal upper extremity and standard occupational therapy was administered. The primary outcome was the change in the Fugl–Meyer assessment (FM) scores, and the secondary outcomes were the changes in the Jebsen–Taylor hand function test (JTT), Purdue pegboard test, and Stroke Impact Scale (SIS) version 3.0 scores. The outcomes were assessed before the intervention, in the middle of the intervention, immediately after the intervention, and 1 month after the intervention.ResultsThe improvements in the FM (FM-total, FM-prox, and FM-dist), JTT (JTT-total and JTT-gross), and SIS (composite and overall SIS, SIS-social participation, and SIS-mobility) scores were significantly greater in the SG group than in the CON group.ConclusionsVR-based rehabilitation combined with standard occupational therapy might be more effective than amount-matched conventional rehabilitation for improving distal upper extremity function and HRQoL.Trial registrationThis study is registered under the title “Effects of Novel Game Rehabilitation System on Upper Extremity Function of Patients With Stroke” and can be located in https://clinicaltrials.gov with the study identifier NCT02029651.
To present user-generated videos that relate to geographic areas for easy access and browsing it is often natural to use maps as interfaces. A common approach is to place thumbnail images of video keyframes in appropriate locations. Here we consider the challenge of determining which keyframes to select and where to place them on the map. Our proposed technique leverages sensor-collected meta-data which are automatically acquired as a continuous stream together with the video. Our approach is able to detect interesting regions and objects (hotspots) and their distances from the camera in a fully automated way. Meaningful keyframes are adaptively selected based on the popularity of the hotspots. Our experiments show very promising results and demonstrate excellent utility for the users.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.