The goal of these studies is to enable persons paralyzed by spinal cord injury (SCI) to drive powered wheelchairs and interact with computers by acting through an interface that utilizes and adapts to their residual upper-body motor capabilities. This is called a """"""""body-machine interface"""""""" because it maps the motions of the upper body -detected by wearable sensors- (arms and shoulders) to the space of device control signals in an optimal way. In this way, paralyzed persons who cannot operate a joystick controller because of lack of hand mobility can effectively use their whole upper body as virtual joystick device. An important characteristic of the proposed approach is that it incorporates an interactive learning process, in which the interface adapts to the subject's mobility and the subject learns to act through the interface. This study aims at developing and testing the customization of this interface to a group of SCI participants with tetraplegia, resulting from hig-level cervical injury. The proposed research is organized in three specific aims:
(Aim 1) To develop new functional capabilities in persons with spinal cord injury by customizing a body- machine interface to their individual upper body mobility. After fitting the interface to the residal movements of each subject, participants will practice computer games aimed at training two classes of control actions: operating a virtual joystick and operating a virtual keyboard. This study will test the ability of the subjects to perform skilled maneuvers with a simulated wheelchair.
(Aim 2.) To test the hypothesis that practicing the upper-body control of personalized interfaces results in significant physical and psychological benefits after spinal-cord injury. Rehabilitation of secondary complications is important in SCI. A study will evaluate and quantify the impact of the practicing functional upper-body motions on the mobility of the shoulder and arms by conventional clinical methods and by measuring the subjects'ability to generate coordinated upper body movements and to apply isometric forces. Other studies under this aim will evaluate the effects of operating the body-machine interface on musculoskeletal pain and on the mood and mental state of the participants.
(Aim 3) To train spinal-cord injury survivors to skillfully operate a powered wheelchair using their enhanced upper body motor skills and customized interface parameters. The goal of this study is to transfer the skills learne in the virtual environment to the control of an actual powered wheelchair. After reaching stable performance in the simulated wheelchair, subjects will practice the control of the physical wheelchair via the same body-machine interface within safe a testing environment. If successful, this study will lead to effective operation of powered wheelchairs using a customized interface that adapts to the residual motor capability of its users. Physical and psychological benefits are expected to derive from the sustained and coordinated activity associated with the use of this body-machine interface
People with tetraplegia often retain some level of mobility of the upper body. The proposed study will develop personalized interfaces, which utilize this residual mobility to enable paralyzed persons to control computers, wheelchairs and other assistive devices. If successful the project will result into the establishment of a new family of human-machine interfaces based on wearable sensors that adapt their functions to their users'abilities.
|Thorp, Elias B; Abdollahi, Farnaz; Chen, David et al. (2016) Upper Body-Based Power Wheelchair Control Interface for Individuals With Tetraplegia. IEEE Trans Neural Syst Rehabil Eng 24:249-60|
|Farshchiansadegh, Ali; Melendez-Calderon, Alejandro; Ranganathan, Rajiv et al. (2016) Sensory Agreement Guides Kinetic Energy Optimization of Arm Movements during Object Manipulation. PLoS Comput Biol 12:e1004861|
|Casadio, Maura; Pressman, Assaf; Mussa-Ivaldi, Ferdinando A (2015) Learning to push and learning to move: the adaptive control of contact forces. Front Comput Neurosci 9:118|
|Summa, S; Pierella, C; Giannoni, P et al. (2015) A body-machine interface for training selective pelvis movements in stroke survivors: A pilot study. Conf Proc IEEE Eng Med Biol Soc 2015:4663-6|
|Pierella, Camilla; Abdollahi, Farnaz; Farshchiansadegh, Ali et al. (2015) Remapping residual coordination for controlling assistive devices and recovering motor functions. Neuropsychologia 79:364-76|
|Jain, Siddarth; Farshchiansadegh, Ali; Broad, Alexander et al. (2015) Assistive Robotic Manipulation through Shared Autonomy and a Body-Machine Interface. IEEE Int Conf Rehabil Robot 2015:526-531|
|Ranganathan, Rajiv; Wieser, Jon; Mosier, Kristine M et al. (2014) Learning redundant motor tasks with and without overlapping dimensions: facilitation and interference effects. J Neurosci 34:8289-99|
|Vato, Alessandro; Szymanski, Francois D; Semprini, Marianna et al. (2014) A bidirectional brain-machine interface algorithm that approximates arbitrary force-fields. PLoS One 9:e91677|
|Pierella, Camilla; Abdollahi, Farnaz; Farshchiansadegh, Ali et al. (2014) Body machine interfaces for neuromotor rehabilitation: a case study. Conf Proc IEEE Eng Med Biol Soc 2014:397-401|
|Farshchiansadegh, Ali; Abdollahi, Farnaz; Chen, David et al. (2014) A body machine interface based on inertial sensors. Conf Proc IEEE Eng Med Biol Soc 2014:6120-4|
Showing the most recent 10 out of 14 publications