Assisting drinking with an affordable BCI-controlled wearable robot and electrical stimulation: a preliminary investigation

• Published in: Journal of neuroengineering and rehabilitation Vol. 11; no. 1; p. 51
• Main Authors: Looned, Ritik, Webb, Jacob, Xiao, Zheng Gang, Menon, Carlo
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 07-04-2014; BioMed Central
• Subjects: Activities of Daily Living; Arm - physiology; Brain research; Brain-Computer Interfaces; Care and treatment; Classification; Design; Diagnosis; Disorders; Drinking; Elbow; Electric Stimulation Therapy - instrumentation; Electric Stimulation Therapy - methods; Electroencephalography; Feasibility Studies; Health aspects; Human-computer interface; Humans; Investigations; Medical research; Nervous system diseases; Nervous System Diseases - rehabilitation; Orthotic Devices; Patient outcomes; Patients; Phases; Rapid prototyping; Rehabilitation; Robotics; Robotics - instrumentation; Robotics - methods; Robots; Spinal cord injuries; Stimulation; Stroke; Stroke (Disease); Strokes; Tasks
• ISSN: 1743-0003; 1743-0003
• DOI: 10.1186/1743-0003-11-51

The aim of the present study is to demonstrate, through tests with healthy volunteers, the feasibility of potentially assisting individuals with neurological disorders via a portable assistive technology for the upper extremities (UE). For this purpose the task of independently drinking a glass of water was selected, as it is one of the most basic and vital activities of the daily living that is unfortunately not achievable by individuals severely affected by stroke.
To accomplish the aim of this study we introduce a wearable and portable system consisting of a novel lightweight Robotic Arm Orthosis (RAO), a Functional Electrical Stimulation (FES) system, and a simple wireless Brain-Computer Interface (BCI). This system is able to process electroencephalographic (EEG) signals and translate them into motions of the impaired arm. Five healthy volunteers participated in this study and were asked to simulate stroke patient symptoms with no voluntary control of their hand and arm. The setup was designed such as the volitional movements of the healthy volunteers' UE did not interfere with the evaluation of the proposed assistive system. The drinking task was split into eleven phases of which seven were executed by detecting EEG-based signals through the BCI. The user was asked to imagine UE motion related to the specific phase of the task to be assisted. Once detected by the BCI the phase was initiated. Each phase was then terminated when the BCI detected the volunteers clenching their teeth.
The drinking task was completed by all five participants with an average time of 127 seconds with a standard deviation of 23 seconds. The incremental motions of elbow extension and elbow flexion were the primary limiting factors for completing this task faster. The BCI control along with the volitional motions also depended upon the users pace, hence the noticeable deviation from the average time.
Through tests conducted with healthy volunteers, this study showed that our proposed system has the potential for successfully assisting individuals with neurological disorders and hemiparetic stroke to independently drink from a glass.