EAGER: An Exploratory Pilot Project to Build an Intelligent Human-Computer Interface System for Neurological Disorder Assessment and Rehabilitation

点击翻译按钮获取中文摘要

In this EAGER the PI will explore issues relating to the development and use of data from game playing for assessment and rehabilitation of neurological disorders. The focus is on Cerebral Palsy (CP), a disease that causes a variety of motor and other impairments. The most common symptoms of CP are a lack of muscle coordination, stiff muscles, exaggerated reflexes, and impaired gait, and treatment includes Physical Therapy (PT) and Occupational Therapy (OT), speech therapy, drugs, surgery, and orthotic devices. Initially, the PI will investigate game-based systems for the upper extremities. Traditionally, OT experts use subjective judgment in conjunction with the Manual Ability Classification System (MACS) to measure the motor skills without connection to cortical level activity. The PI's approach is to connect cortical activity with motor activity. She will explore the coupling and integration of computer games and wearable sensors for both neurological and motor assessment testing, as well as for long-term rehabilitation at home. In particular, she will design a family of computer games that correspond to OT exercises and build an initial set of feature classifiers for types of CP with motor skill assessment. She will also build computer infrastructure for remote rehabilitation and a cyclical evaluation methodology. The primary outcome of this research will be an initial setup for remote rehabilitation that uses machine reinforcement learning and fuses multimodal information collected from a variety of sensors. Using computer games in conjunction with brain imaging and traditional rehabilitation outcomes is a radical and untested but potentially transformative approach to healthcare practices for chronic conditions such as CP.Broader Impacts: The PI's long-term goal is to develop an intelligent system called CPLAY, whose front end is a set of computer games to provide controlled stimuli to children with CP in order to facilitate a desired motor response and generate performance data for diagnosis and rehabilitation treatment. CPLAY's backend will be a set of computational engines to enable data logging (from a child playing the game), data fusion, analysis and decision support. The @lab version of CPLAY will be used for functional near infrared (fNIR) imaging, while the @home version will be used for rehabilitation with various additional sensors capturing and fusing data during game playing. The fNIR imaging is used to determine neuro-plasticity and motor recovery. The @home version tracks performance over time, considers context of the game, and can be monitored remotely if needed. Both versions will allow for game adjustments to provide personalized treatment. The CPLAY approach promises to lower costs and facilitate family engagement in the rehabilitation. Project outcomes will include a paradigm, methodology and tools with broad applicability to other neurological disorders.