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Electrical Stimulation and Methods to Manipulate the Motor and Sensory System: Current Settings and Applications

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

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 7938

Special Issue Editor

Dr. Dimitrios A. Patikas

E-Mail Website
Guest Editor
School of Physical Education and Sports Science at Serres, Aristotle University of Thessaloniki, 621 10 Thessaloniki, Greece
Interests: neuromuscular control; balance; training; electrical stimulation; electromyography; reflexes; fatigue; aging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Electrical stimulation is an old but still developing technique used to manipulate the function of the neuromuscular system. Rehabilitation, training, and virtual reality are only some of the fields in which electrical stimulation has been applied in different areas of the body, stimulating the skin, muscles, nerves, and the brain. In recent decades, we have learned more about the plasticity of the central nervous system and the capacity of the muscles to adapt to external stimuli, and several other methods have been developed and used to stimulate the neuromuscular system and document its responses. Haptic stimulation or vibration (tendon or whole body) are additional techniques that can be used as standalone or in combination with other stimulation methods to create illusions or to regulate the sensory flow.

This Special Issue focuses on current methods and techniques used to manipulate the sensory inflow of information and the motor output of the neuromuscular system, placing particular emphasis on the devices and applications that are currently available and their perspectives for the future. Both review articles and original research papers are solicited.

Dr. Dimitrios A. Patikas
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • neuromuscular electrical stimulation
  • nerve stimulation
  • tendon vibration
  • whole body vibration
  • functional electrical stimulation
  • TENS
  • galvanic vestibular stimulation
  • transcranial magnetic stimulation
  • sensory stimulation

Published Papers (2 papers)

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Research

17 pages, 4354 KiB  
Article
Methods for Lowering the Power Consumption of OS-Based Adaptive Deep Brain Stimulation Controllers
by Roberto Rodriguez-Zurrunero, Alvaro Araujo and Madeleine M. Lowery
Sensors 2021, 21(7), 2349; https://doi.org/10.3390/s21072349 - 28 Mar 2021
Cited by 7 | Viewed by 2733
Abstract
The identification of a new generation of adaptive strategies for deep brain stimulation (DBS) will require the development of mixed hardware–software systems for testing and implementing such controllers clinically. Towards this aim, introducing an operating system (OS) that provides high-level features (multitasking, hardware [...] Read more.
The identification of a new generation of adaptive strategies for deep brain stimulation (DBS) will require the development of mixed hardware–software systems for testing and implementing such controllers clinically. Towards this aim, introducing an operating system (OS) that provides high-level features (multitasking, hardware abstraction, and dynamic operation) as the core element of adaptive deep brain stimulation (aDBS) controllers could expand the capabilities and development speed of new control strategies. However, such software frameworks also introduce substantial power consumption overhead that could render this solution unfeasible for implantable devices. To address this, in this work four techniques to reduce this overhead are proposed and evaluated: a tick-less idle operation mode, reduced and dynamic sampling, buffered read mode, and duty cycling. A dual threshold adaptive deep brain stimulation algorithm for suppressing pathological oscillatory neural activity was implemented along with the proposed energy saving techniques on an energy-efficient OS, YetiOS, running on a STM32L476RE microcontroller. The system was then tested using an emulation environment coupled to a mean field model of the parkinsonian basal ganglia to simulate local field potential (LFPs) which acted as a biomarker for the controller. The OS-based controller alone introduced a power consumption overhead of 10.03 mW for a sampling rate of 1 kHz. This was reduced to 12 μW by applying the proposed tick-less idle mode, dynamic sampling, buffered read and duty cycling techniques. The OS-based controller using the proposed methods can facilitate rapid and flexible testing and implementation of new control methods. Furthermore, the approach has the potential to become a central element in future implantable devices to enable energy-efficient implementation of a wide range of control algorithms across different neurological conditions and hardware platforms. Full article
(This article belongs to the Special Issue Electrical Stimulation and Methods to Manipulate the Motor and Sensory System: Current Settings and Applications)
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21 pages, 5735 KiB  
Article
Electrically Elicited Force Response Characteristics of Forearm Extensor Muscles for Electrical Muscle Stimulation-Based Haptic Rendering
by Jungeun Lee, Yeongjin Kim and Hoeryong Jung
Sensors 2020, 20(19), 5669; https://doi.org/10.3390/s20195669 - 4 Oct 2020
Cited by 6 | Viewed by 4211
Abstract
A haptic interface based on electrical muscle stimulation (EMS) has huge potential in terms of usability and applicability compared with conventional haptic interfaces. This study analyzed the force response characteristics of forearm extensor muscles for EMS-based haptic rendering. We introduced a simplified mathematical [...] Read more.
A haptic interface based on electrical muscle stimulation (EMS) has huge potential in terms of usability and applicability compared with conventional haptic interfaces. This study analyzed the force response characteristics of forearm extensor muscles for EMS-based haptic rendering. We introduced a simplified mathematical model of the force response, which has been developed in the field of rehabilitation, and experimentally validated its feasibility for haptic applications. Two important features of the force response, namely the peak force and response time, with respect to the frequency and amplitude of the electrical stimulation were identified by investigating the experimental force response of the forearm extensor muscles. An exponential function was proposed to estimate the peak force with respect to the frequency and amplitude, and it was verified by comparing with the measured peak force. The response time characteristics were also examined with respect to the frequency and amplitude. A frequency-dependent tendency, i.e., an increase in response time with increasing frequency, was observed, whereas there was no correlation with the amplitude. The analysis of the force response characteristics with the application of the proposed force response model may help enhance the fidelity of EMS-based haptic rendering. Full article
(This article belongs to the Special Issue Electrical Stimulation and Methods to Manipulate the Motor and Sensory System: Current Settings and Applications)
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