Effect of exergaming with active passive trainer on lower extremity functions in patients with stroke: A pilot randomized controlled trial

Patients with stoke will be included in the study trial if they met the inclusion criteria. The written and oral consent of all patients will be taken, and procedure will be explained. Demographic data will be noted. Patients will be screened according to inclusion and exclusion criteria and eligible participants will be included in the study. Before collection of the data, patients will be explained about the study aim and procedure in detail and informed written consent will be obtained from the patients. The participants will be interviewed and the information will be gathered about their demographic data, health related information like past medical history, duration since stroke, investigations. The Pre assessment data will be obtained using Fugl-Meyer scale for lower limb, Time up and go test, 6-minute walk test and functional independence scale. Participants will divide into two groups intervention group and control group using a computer generated numbers. The intervention will be given for 5 days/ week for 6 weeks(21,29). The intervention will include a 20-45minute exergaming session with active passive trainer, followed by a conventional therapy session. In this study, we will utilize an Active Passive Trainer (Kinetic Kinevia) in conjunction with a laptop running the Zwift application. The Zwift application, preinstalled on the laptop, offers a user-friendly interface allowing navigation through various virtual worlds such as Watopia, a fictional island, and customization of avatars. Zwift tracks various performance metrics, such as distance, speed, and power output, allowing patients to monitor their progress over time and set goals for improvement. Experience points are earned by completing rides, races, or other activities in Zwift. As users accumulate XP, they level up and unlock new virtual items, routes, and challenges. Leveling up can also provide access to advanced training plans and workouts. Experience points are earned by completing rides, workouts, races, or other activities in Zwift.  Speed sensors will be affixed to the patient’s paretic limb using a strap, establishing wireless communication with the Zwift application on the laptop through Bluetooth connectivity. These sensors will detect movement patterns as the patient pedals, facilitating the synchronization of the avatar’s speed within the virtual environment to correspond with the patient’s pedaling speed. This alignment of the avatar’s speed and the patient’s actual pedaling motion will significantly enhance the immersive experience, fostering improved concentration and engagement during training sessions. Data collection will be done before 1st week of intervention and at the end of 6thweek of intervention. Data will be entered in Microsoft Excel analyzed using SPSS (Statistical Package for Social Science) version 27.0 and graph pad prism 7.0 version. The data will be represented in the form of visual impression like line diagram, bar diagram and statistical analysis will be done .