Estimating Exerted Hand Force via Force Myography to Interact with a Biaxial Stage in Real-Time by Learning Human Intentions: A Preliminary Investigation

Force myography (FMG) signals can read volumetric changes of muscle movements, while a human participant interacts with the environment. For collaborative activities, FMG signals could potentially provide a viable solution to controlling manipulators. In this paper, a novel method to interact with a two-degree-of-freedom (DoF) system consisting of two perpendicular linear stages using FMG is investigated. The method consists in estimating exerted hand forces in dynamic arm motions of a participant using FMG signals to provide velocity commands to the biaxial stage during interactions. Five different arm motion patterns with increasing complexities, i.e., “x-direction”, “y-direction”, “diagonal”, “square”, and “diamond”, were considered as human intentions to manipulate the stage within its planar workspace. FMG-based force estimation was implemented and evaluated with a support vector regressor (SVR) and a kernel ridge regressor (KRR). Real-time assessments, where 10 healthy participants were asked to interact with the biaxial stage by exerted hand forces in the five intended arm motions mentioned above, were conducted. Both the SVR and the KRR obtained higher estimation accuracies of 90–94% during interactions with simple arm motions (x-direction and y-direction), while for complex arm motions (diagonal, square, and diamond) the notable accuracies of 82–89% supported the viability of the FMG-based interactive control.

Effect of Repositioning Aids and Patient Weight on Biomechanical Stresses When Repositioning Patients in Bed

Objective The aim of the study was to estimate the risk of injury when repositioning patients of different weight with commonly used repositioning aids. Background Repositioning dependent patients in bed is the most common type of patient handling activity and is associated with high rates of musculoskeletal disorders in healthcare workers. Several studies have evaluated repositioning aids, but typically for a single patient weight and often without estimating risk of injury based on biomechanical analysis. Method Ten nurses performed four repositioning activities on three participants (50, 77, 141 kg) using three repositioning aids (pair of friction-reducing sheets [FRS], turn and position glide sheet, air-assisted transfer device) and a draw sheet. Motion capture, hand forces, and ground reaction forces were recorded. Spine loading was estimated using a dynamic biomechanical model. Results Hand forces and spine compression exceeded recommended limits for most patient weights and repositioning tasks with the draw sheet. FRS and glide sheet reduced these loads but still exceeded recommended limits for all but the 50-kg patient. Only the air-assisted transfer device reduced forces to accepted levels for all patient weights. Physical stresses were relatively low when turning patients. Conclusion Most repositioning aids are insufficient to properly mitigate risk of musculoskeletal injury in healthcare workers. Only the air-assisted transfer device was sufficient to adequately mitigate the risk of injury when moving patients of average or above-average weight. Application To safely move dependent patients, a robust solution requires mechanical lifts and may utilize air-assisted transfer devices for patient transfers.

Hand forces and placement are modulated and covary during anticipatory control of bimanual manipulation

Dexterous object manipulation relies on the feedforward and feedback control of kinetics (forces) and kinematics (hand shaping and digit placement). Lifting objects with an uneven mass distribution involves the generation of compensatory moments at object lift-off to counter object torques. This is accomplished through the modulation and covariation of digit forces and placement, which has been shown to be a general feature of unimanual manipulation. These feedforward anticipatory processes occur before performance-specific feedback. Whether this adaptation is a feature unique to unimanual dexterous manipulation or general across unimanual and bimanual manipulation is not known. We investigated the generation of compensatory moments through hand placement and force modulation during bimanual manipulation of an object with variable center of mass. Participants were instructed to prevent object roll during the lift. Similar to unimanual grasping, we found modulation and covariation of hand forces and placement for successful performance. Thus this motor adaptation of the anticipatory control of compensatory moment is a general feature across unimanual and bimanual effectors. Our results highlight the involvement of high-level representation of manipulation goals and underscore a sensorimotor circuitry for anticipatory control through a continuum of force and placement modulation of object manipulation across a range of effectors. NEW & NOTEWORTHY This is the first study, to our knowledge, to show that successful bimanual manipulation of objects with asymmetrical centers of mass is performed through the modulation and covariation of hand forces and placements to generate compensatory moments. Digit force-to-placement modulation is thus a general phenomenon across multiple effectors, such as the fingers of one hand, and both hands. This adds to our understanding of integrating low-level internal representations of object properties into high-level task representations.