<b>Human Sitting to Walking Transitions: A Motion Capture Dataset</b>

Sit-to-walk (STW) is a crucial activity of daily living that involves a seamless merging between sit-to-stand (STS) transitions and gait. Due to ageing or movement impairment the ability to perform STW may deteriorate leading to an increased fall risk along with physical and psychological degradation. Therefore, it is necessary to assist impaired individuals during STW, to preserve independence and a high quality of life. Consequently, understanding STW biomechanics and execution strategies would aid in rehabilitation, through assistive devices or interventions. STW biomechanical trajectories of healthy adults can serve as a reference or benchmark to assess and aid neuromusculoskeletal impairments, while also monitoring recovery progress. As such, this study presents a publicly available dataset containing lower body motion capture (Mocap), ground reaction force, inertial measurement unit (IMU) and surface electromyography (SEMG) data for healthy adults, during STW. Additionally, the KOOS survey was conducted for knee health information, while STW was obtained via the timed-up-and-go test. The dataset had a sample size of 65 subjects with 32 males and 33 females, within three age groups – young, middle-aged, and older adults. The average subject age, weight and height were 39.35 ± 17.51 years, 63.69 ± 15.35 kg and 162.81 ± 9.51 cm, respectively. Moreover, to validate the dataset the hip, knee and ankle joint angles were derived (using Mocap data) along with the processed and normalised SEMG (using the maximal voluntary contraction) of 8 muscles, via OpenSim 4.2 and MATLAB (MathWorks). These were compared with existing literature for STW/STS and showed a match in both overall trends and range, thus validating the collected experimental data.