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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 8343

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Special Issue Editors

Dr. Christine Azevedo Coste

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Guest Editor

Camin Lab, INRIA, Montpellier, France
Interests: assistive technologies; functional electrical stimulation (FES); movement analysis; neuroprosthetic devices

Dr. Lucas Oliveira da Fonseca

E-Mail Website
Guest Editor

Camin lab, INRIA, Montpellier, France
Interests: biomedical engineering; rehabilitation engineering; movement restoration; movement analysis; machine learning; inertial measurements; real time applications

Special Issue Information

Dear Colleagues,

Hundreds of millions of people live with some kind of motor disability. Some devices have long been life-changing alternatives for these individuals, such as wheelchairs or prostheses. However, seldom do these solutions restore the level of independence an able-bodied person possesses.

Novel technologies are being developed to assist movement in individuals with motor deficiencies, such as active orthosis, exoskeletons and robotic prosthesis. In this context, acquiring reliable and useful information from these systems remains one of the critical issues in the field of assistive technologies. Embedding sensors able to inform controllers or users on the ongoing movement execution or on the forces and torques involved is not trivial. This is particularly true in real-life scenarios like rehabilitation clinics and patient daily lives. State-of-the-art studies indicate that current challenges also involve precise movement and force closed-loop control and user bio-feedback.

The purpose of this Special Issue is to present recent advances in sensor design and data processing techniques to provide information to users and controllers of assistive technology devices.

Authors are welcome to submit papers related to the following topics:

Sensor design and development in the context of assistive technologies in motor deficiencies;
Instrumentation of exoskeletons, prostheses, neuroprostheses, and orthoses to enhance motor assistance;
Interpretation of neural or muscular information in the control of rehabilitation devices;
Sensor data processing for user intention recognition;
Sensor data processing for user bio-feedback.

Dr. Christine Azevedo Coste
Dr. Lucas Oliveira da Fonseca
Guest Editors

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Keywords

Motor restoration
Neurorehabilitation
Biomedical engineering
Assistive technologies
Wearable sensors
Functional electrical stimulation
Robotics

Published Papers (4 papers)

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Research

27 pages, 3201 KiB

Open AccessArticle

Designing Ecological Auditory Feedback on Lower Limb Kinematics for Hemiparetic Gait Training

by Prithvi Ravi Kantan, Sofia Dahl, Helle Rovsing Jørgensen, Chetali Khadye and Erika G. Spaich

Sensors 2023, 23(8), 3964; https://0-doi-org.brum.beds.ac.uk/10.3390/s23083964 - 13 Apr 2023

Viewed by 1588

Abstract

Auditory feedback has earlier been explored as a tool to enhance patient awareness of gait kinematics during rehabilitation. In this study, we devised and tested a novel set of concurrent feedback paradigms on swing phase kinematics in hemiparetic gait training. We adopted a user-centered design approach, where kinematic data recorded from 15 hemiparetic patients was used to design three feedback algorithms (wading sounds, abstract, musical) based on filtered gyroscopic data from four inexpensive wireless inertial units. The algorithms were tested (hands-on) by a focus group of five physiotherapists. They recommended that the abstract and musical algorithms be discarded due to sound quality and informational ambiguity. After modifying the wading algorithm (as per their feedback), we conducted a feasibility test involving nine hemiparetic patients and seven physiotherapists, where variants of the algorithm were applied to a conventional overground training session. Most patients found the feedback meaningful, enjoyable to use, natural-sounding, and tolerable for the typical training duration. Three patients exhibited immediate improvements in gait quality when the feedback was applied. However, minor gait asymmetries were found to be difficult to perceive in the feedback, and there was variability in receptiveness and motor change among the patients. We believe that our findings can advance current research in inertial sensor-based auditory feedback for motor learning enhancement during neurorehabilitation. Full article

(This article belongs to the Special Issue Sensors for Artificial Movement Control)

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14 pages, 3917 KiB

Open AccessArticle

ICEP: An Instrumented Cycling Ergometer Platform for the Assessment of Advanced FES Strategies

by Petar Kajganic, Vance Bergeron and Amine Metani

Sensors 2023, 23(7), 3522; https://0-doi-org.brum.beds.ac.uk/10.3390/s23073522 - 28 Mar 2023

Viewed by 1277

Abstract

Background: Functional electrical stimulation (FES) cycling has seen an upsurge in interest over the last decade. The present study describes the novel instrumented cycling ergometer platform designed to assess the efficiency of electrical stimulation strategies. The capabilities of the platform are showcased in an example determining the adequate stimulation patterns for reproducing a cycling movement of the paralyzed legs of a spinal cord injury (SCI) subject. Methods: Two procedures have been followed to determine the stimulation patterns: (1) using the EMG recordings of the able-bodied subject; (2) using the recordings of the forces produced by the SCI subject’s stimulated muscles. Results: the stimulation pattern derived from the SCI subject’s force output was found to produce 14% more power than the EMG-derived stimulation pattern. Conclusions: the cycling platform proved useful for determining and assessing stimulation patterns, and it can be used to further investigate advanced stimulation strategies. Full article

(This article belongs to the Special Issue Sensors for Artificial Movement Control)

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23 pages, 6497 KiB

Open AccessArticle

Design and Fabrication of Embroidered Textile Strain Sensors: An Alternative to Stitch-Based Strain Sensors

by Jose Guillermo Colli Alfaro and Ana Luisa Trejos

Sensors 2023, 23(3), 1503; https://0-doi-org.brum.beds.ac.uk/10.3390/s23031503 - 29 Jan 2023

Cited by 5 | Viewed by 2862

Abstract

Smart textile sensors have been gaining popularity as alternative methods for the continuous monitoring of human motion. Multiple methods of fabrication for these textile sensors have been proposed, but the simpler ones include stitching or embroidering the conductive thread onto an elastic fabric to create a strain sensor. Although multiple studies have demonstrated the efficacy of textile sensors using the stitching technique, there is almost little to no information regarding the fabrication of textile strain sensors using the embroidery method. In this paper, a design guide for the fabrication of an embroidered resistive textile strain sensor is presented. All of the required design steps are explained, as well as the different embroidery design parameters and their optimal values. Finally, three embroidered textile strain sensors were created using these design steps. These sensors are based on the principle of superposition and were fabricated using a stainless-steel conductive thread embroidered onto a polyester–rubber elastic knit structure. The three sensors demonstrated an average gauge factor of

1.88 \pm 0.51

over a 26% working range, low hysteresis (

8.54 \pm 2.66 %

), and good repeatability after being pre-stretched over a certain number of stretching cycles. Full article

(This article belongs to the Special Issue Sensors for Artificial Movement Control)

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17 pages, 16639 KiB

Open AccessArticle

Earable Ω (OMEGA): A Novel Clenching Interface Using Ear Canal Sensing for Human Metacarpophalangeal Joint Control by Functional Electrical Stimulation

by Kazuhiro Matsui, Yuya Suzuki, Keita Atsuumi, Miwa Nagai, Shotaro Ohno, Hiroaki Hirai, Atsushi Nishikawa and Kazuhiro Taniguchi

Sensors 2022, 22(19), 7412; https://0-doi-org.brum.beds.ac.uk/10.3390/s22197412 - 29 Sep 2022

Viewed by 1295

Abstract

(1) Background: A mouth-free interface is required for functional electrical stimulation (FES) in people with spinal cord injuries. We developed a novel system for clenching the human metacarpophalangeal (MP) joint using an earphone-type ear canal movement sensor. Experiments to control joint angle and joint stiffness were performed using the developed system. (2) Methods: The proposed FES used an equilibrium point control signal and stiffness control signal: electrical agonist–antagonist ratio and electrical agonist–antagonist sum. An angle sensor was used to acquire the joint angle, and system identification was utilized to measure joint stiffness using the external force of a robot arm. Each experiment included six and five subjects, respectively. (3) Results: While the joint angle could be controlled well by clenching with some hysteresis and delay in three subjects, it could not be controlled relatively well after hyperextension in the other subjects, which revealed a calibration problem and a change in the characteristics of the human MP joint caused by hyperextension. The joint stiffness increased with the clenching amplitude in five subjects. In addition, the results indicated that viscosity can be controlled. (4) Conclusions: The developed system can control joint angle and stiffness. In future research, we will develop a method to show that this system can control the equilibrium point and stiffness simultaneously. Full article

(This article belongs to the Special Issue Sensors for Artificial Movement Control)

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