An evaluation of sit to stand devices for use in rehabilitation

There are many assistive devices to help with raising a person from a seat. These devices are considered active as they require some balance, trunk control and weightbearing ability. There is concern that this movement is mostly passive due to fixation at the trunk and knee. This study explores the movement patterns in sit to stand transfers active and assisted. Study Design: A fully squared repeated measures design was use. All participants (n = 20) used all conditions (n = 7) in a balanced order. Transfers were recorded with; video recordings, a 6 dimensional force plate, hip, knee and ankle positions were recorded with motion capture. Subjective evaluations for comfort and security were completed. Physical data was compared with ANOVA calculations with Bonferroni corrections. Results: Device G scored highest for comfort, knee support and overall preference. Sling movement had a negative effect on the sensations of comfort and security. The motion analysis of the flexible knee support showed: People push into the floor and CoP moved towards the toe.More anterior knee movement (P < 0.05).More bodyweight through feet (P < 0.05).Quicker transfer of weight onto feet.Very low bodyweight was recorded in all lowering actions. The use of a flexible knee support raised the subjective and physical performance of the assistive device and may improve rehabilitation responses

Human sit-to-stand transfer modeling towards intuitive and biologically-inspired robot assistance

© 2016, Springer Science+Business Media New York. Sit-to-stand (STS) transfers are a common human task which involves complex sensorimotor processes to control the highly nonlinear musculoskeletal system. In this paper, typical unassisted and assisted human STS transfers are formulated as optimal feedback control problem that finds a compromise between task end-point accuracy, human balance, energy consumption, smoothness of motion and control and takes further human biomechanical control constraints into account. Differential dynamic programming is employed, which allows taking the full, nonlinear human dynamics into consideration. The biomechanical dynamics of the human is modeled by a six link rigid body including leg, trunk and arm segments. Accuracy of the proposed modelling approach is evaluated for different human healthy and patient/elderly subjects by comparing simulations and experimentally collected data. Acceptable model accuracy is achieved with a generic set of constant weights that prioritize the different criteria. Finally, the proposed STS model is used to determine optimal assistive strategies suitable for either a person with specific body segment weakness or a more general weakness. These strategies are implemented on a robotic mobility assistant and are intensively evaluated by 33 elderlies, mostly not able to perform unassisted STS transfers. The validation results show a promising STS transfer success rate and overall user satisfaction