Case study: Head orientation and neck electromyography for cursor control in persons with high cervical tetraplegia

Abstract

Abstract-We evaluated the ability of an individual with a high cervical spinal cord injury (SCI) to control a cursor on a computer screen using two different user interfaces: (1) head movements measured via a head-mounted orientation sensor and (2) electromyography (EMG) signals from four head and neck muscles acquired using a 4-channel implanted upper-limb neuroprosthesis that had been deployed in an earlier study. The subject moved the cursor to a set of targets on the screen in a two-dimensional, center-out, target-acquisition task, and his performance was evaluated with a variety of performance measures to assess both position and velocity control accuracy. The subject's performance with both command sources was also compared with the performance of a group of nondisabled subjects. Head orientation provided more accurate performance but was less responsive than EMG. Both command sources showed some directionally dependent performance, with movement to diagonally located targets being performed by a series of sequential motions rather than via straight paths. Overall, the SCI subject's performance with each command source was similar to that reported for a nondisabled population using the same interfaces and performing the same task.

Hands-Free Human-Computer Interface Based on Facial Myoelectric Pattern Recognition

“…Different from conventional mapping schemes, facial movements were detected and classified using myoelectric pattern recognition algorithms, and mapped to cursor actions in our design. By using such a mapping scheme, only three EMG channels were needed to control the cursor movement in four directions, compared with recent studies in which four EMG channels were necessary (2, 3, 9). By using only four EMG channels in our design, full control of a cursor (including movement in four directions, click, and drag & drop) was implemented.…”

“…The speed of cursor movement is usually controlled by the amplitude of the user's EMG signals when conventional channel-based mapping scheme is applied (2, 9). In our design, the speed was constant, so that the user can pay more attention to the movement pattern.…”

“…According to Fitts's law (9), the time required to move the cursor from one screen key to the target screen key is a function of the task's Index of Difficulty (ID). ID can be estimated using the distance and the width of the target screen key (9).…”

“…According to Fitts's law (9), the time required to move the cursor from one screen key to the target screen key is a function of the task's Index of Difficulty (ID). ID can be estimated using the distance and the width of the target screen key (9). In order to quantify the relation between movement time and ID, four horizontal movements (e.g., from “f” to “a” on the screen keyboard) were picked out as samples to perform a linear fitting.…”

“…Human facial movements have been established to be reliable input to a variety of machines including electronic devices (1–6) and assistive devices (7, 8). Such kind of human-machine interface provides an easy and intuitive approach to interacting with electronic devices for users with limited hand function (9). As a result, they have improved accessibility to the digital world and better user experience.…”