Non-invasive control interfaces for intention detection in active movement-assistive devices

Abstract

Active movement-assistive devices aim to increase the quality of life for patients with neuromusculoskeletal disorders. This technology requires interaction between the user and the device through a control interface that detects the user’s movement intention. Researchers have explored a wide variety of invasive and non-invasive control interfaces. To summarize the wide spectrum of strategies, this paper presents a comprehensive review focused on non-invasive control interfaces used to operate active movement-assistive devices. A novel systematic classification method is proposed to categorize the control interfaces based on: (I) the source of the physiological signal, (II) the physiological phenomena responsible for generating the signal, and (III) the sensors used to measure the physiological signal. The proposed classification method can successfully categorize all the existing control interfaces providing a comprehensive overview of the state of the art. Each sensing modality is briefly described in the body of the paper following the same structure used in the classification method. Furthermore, we discuss several design considerations, challenges, and future directions of non-invasive control interfaces for active movement-assistive devices.Electronic supplementary materialThe online version of this article (doi:10.1186/1743-0003-11-168) contains supplementary material, which is available to authorized users.

Control interfaces to actively support the arm function of men with Duchenn Muscular Dystrophy

“…Pilot trials showed that this measurement-based method was able to accurately estimate gravity and joint stiffness forces along the range of motion of the elbow. A video showing the compensation force measurement can be found in [249] as additional file 4. Figure 29 shows the control diagram of the physiological (i.e.…”

“…The target angles located near the limits of the ROM were placed, within the ROM, 5 degrees from the limits in order to prevent collisions with the mechanical end-stops placed at the limits of the ROM. A video of one of the participants performing the discrete position-tracking task using the force-based control interface can be found in [249] as additional file 5.…”

“…To control such devices, the user needs a way to communicate his motion intention to the device through a control interface [249]. In our previous work [262] we investigated the feasibility of using surface electromyography (EMG) and force-based control with active gravity and joint-stiffness compensation.…”

“…The selection of the control interface, in response to specific user needs and capabilities, is a crucial determinant of the usability of the assistive device. We consider that surface elcectromyography (EMG) and force-based interfaces are two promising strategies to achieve a natural control of active arm supports as they have been widely implemented in prostheses and orthoses/exoskeletons [249,33].…”

“…We consider that the use of control interfaces that detect the motion intention from physiological signals that are implicitly related to the supported motion can result in a more natural and intuitive interaction with the robotic arm support. In this direction, we have developed and evaluated force-and surface electromyography-(EMG) based control interfaces [249,262].…”