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Special Issue "Multi-Sensor-Based Intelligent Systems for Physical Rehabilitation"

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

Deadline for manuscript submissions: closed (15 June 2019).

Special Issue Editors

Prof. Dr. Chin-Feng Lai
Website
Guest Editor
Department of Engineering Science, National Cheng Kung University, Tainan 701, Taiwan
Department of Computer Science and Information Engineering, National Chung Cheng University, Min-Hsiung Chia-Yi 621, Taiwan
Interests: Internet of Things; body sensor networks; e-healthcare; mobile cloud computing; cloud-assisted multimedia network; embedded systems, etc.
Prof. Dr. Laurence T. Yang
Website
Guest Editor
Department of Computer Science, St. Francis Xavier University, Antigonish, Canada
Interests: parallel and distributed computing; embedded and ubiquitous/pervasive computing
Special Issues and Collections in MDPI journals
Prof. Dr. Yu-Sheng Su
Website
Guest Editor
Research Center for Advanced Science and Technology, National Central University, Taoyuan 32001, Taiwan
Department of Computer Science & Information Engineering, National Central University, Taoyuan 32001, Taiwan
Interests: Internet of Things; cloud computing; big data analysis; embedded systems; deep learning, etc.

Special Issue Information

Dear Colleagues,

Recently, many serious trends are emerging, including population aging, low birth rates and a lack of medical resources, which affect governments’ ability to manage healthcare. The intersection of these trends poses issues and challenges to physical rehabilitation. Meanwhile, rapid cognitive and intelligence systems and infrastructures have been developed to provide people with smarter and more efficient physical rehabilitation services. However, it is difficult to achieve greater intelligence depending on the existing techniques and models. Constructing a theoretical framework for advanced improvements to physical rehabilitation has become a critical issue. This Special Issue will provide a platform to collect novel research results and experiments on physical rehabilitation topics related to multi-sensor-based intelligent systems and other related sensor fields. This Special Issue features all recent advances, highlighting the trends with regard to advanced theory, systems and applications on physical rehabilitation issues.

Prof. Dr. Chin-Feng Lai
Prof. Dr. Laurence T. Yang
Prof. Dr. Yu-Sheng Su
Guest Editors

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 papers will be 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 2000 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

  • Wearable sensors
  • E-healthcare
  • Deep learning and machine learning techniques
  • Multimodal information fusion
  • Intelligent signal processing
  • Physical rehabilitation
  • Intelligent medical systems
  • Sensorized medical devices

Published Papers (5 papers)

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Research

Open AccessArticle
Assisted Grasping in Individuals with Tetraplegia: Improving Control through Residual Muscle Contraction and Movement
Sensors 2019, 19(20), 4532; https://doi.org/10.3390/s19204532 - 18 Oct 2019
Cited by 1
Abstract
Individuals who sustained a spinal cord injury often lose important motor skills, and cannot perform basic daily living activities. Several assistive technologies, including robotic assistance and functional electrical stimulation, have been developed to restore lost functions. However, designing reliable interfaces to control assistive [...] Read more.
Individuals who sustained a spinal cord injury often lose important motor skills, and cannot perform basic daily living activities. Several assistive technologies, including robotic assistance and functional electrical stimulation, have been developed to restore lost functions. However, designing reliable interfaces to control assistive devices for individuals with C4–C8 complete tetraplegia remains challenging. Although with limited grasping ability, they can often control upper arm movements via residual muscle contraction. In this article, we explore the feasibility of drawing upon these residual functions to pilot two devices, a robotic hand and an electrical stimulator. We studied two modalities, supra-lesional electromyography (EMG), and upper arm inertial sensors (IMU). We interpreted the muscle activity or arm movements of subjects with tetraplegia attempting to control the opening/closing of a robotic hand, and the extension/flexion of their own contralateral hand muscles activated by electrical stimulation. Two groups were recruited: eight subjects issued EMG-based commands; nine other subjects issued IMU-based commands. For each participant, we selected at least two muscles or gestures detectable by our algorithms. Despite little training, all participants could control the robot’s gestures or electrical stimulation of their own arm via muscle contraction or limb motion. Full article
(This article belongs to the Special Issue Multi-Sensor-Based Intelligent Systems for Physical Rehabilitation)
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Open AccessArticle
FES-Induced Cycling in Complete SCI: A Simpler Control Method Based on Inertial Sensors
Sensors 2019, 19(19), 4268; https://doi.org/10.3390/s19194268 - 01 Oct 2019
Abstract
This article introduces a novel approach for a functional electrical stimulation (FES) controller intended for FES-induced cycling based on inertial measurement units (IMUs). This study aims at simplifying the design of electrical stimulation timing patterns while providing a method that can be adapted [...] Read more.
This article introduces a novel approach for a functional electrical stimulation (FES) controller intended for FES-induced cycling based on inertial measurement units (IMUs). This study aims at simplifying the design of electrical stimulation timing patterns while providing a method that can be adapted to different users and devices. In most of studies and commercial devices, the crank angle is used as an input to trigger stimulation onset. We propose instead to use thigh inclination as the reference information to build stimulation timing patterns. The tilting angles of both thighs are estimated from one inertial sensor located above each knee. An IF–THEN rule algorithm detects, online and automatically, the thigh peak angles in order to start and stop the stimulation of quadriceps muscles, depending on these events. One participant with complete paraplegia was included and was able to propel a recumbent trike using the proposed approach after a very short setting time. This new modality opens the way for a simpler and user-friendly method to automatically design FES-induced cycling stimulation patterns, adapted to clinical use, for multiple bike geometries and user morphologies. Full article
(This article belongs to the Special Issue Multi-Sensor-Based Intelligent Systems for Physical Rehabilitation)
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Open AccessArticle
A RGBD-Based Interactive System for Gaming-Driven Rehabilitation of Upper Limbs
Sensors 2019, 19(16), 3478; https://doi.org/10.3390/s19163478 - 09 Aug 2019
Cited by 4
Abstract
Current physiotherapy services may not be effective or suitable for certain patients due to lack of motivation, poor adherence to exercises, insufficient supervision and feedback or, in the worst case, refusal to continue with the rehabilitation plan. This paper introduces a novel approach [...] Read more.
Current physiotherapy services may not be effective or suitable for certain patients due to lack of motivation, poor adherence to exercises, insufficient supervision and feedback or, in the worst case, refusal to continue with the rehabilitation plan. This paper introduces a novel approach for rehabilitation of upper limbs through KineActiv, a platform based on Microsoft Kinect v2 and developed in Unity Engine. KineActiv proposes exergames to encourage patients to perform rehabilitation exercises prescribed by a specialist, controls the patient′s performance, and corrects execution errors on the fly. KineActiv comprises a web platform where the physiotherapist can review session results, monitor patient health, and adjust rehabilitation routines. We recruited 10 patients for assessing the system usability as well as the system performance. Results show that KineActiv is a usable, enjoyable and reliable system, that does not cause any negative feelings. Full article
(This article belongs to the Special Issue Multi-Sensor-Based Intelligent Systems for Physical Rehabilitation)
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Open AccessArticle
Development of a Dynamic Oriented Rehabilitative Integrated System (DORIS) and Preliminary Tests
Sensors 2019, 19(15), 3402; https://doi.org/10.3390/s19153402 - 02 Aug 2019
Cited by 1
Abstract
Moving platforms were introduced in the field of the study of posturography since the 1970s. Commercial platforms have some limits: a limited number of degrees of freedom, pre-configured protocols, and, usually, they are expensive. In order to overcome these limits, we developed a [...] Read more.
Moving platforms were introduced in the field of the study of posturography since the 1970s. Commercial platforms have some limits: a limited number of degrees of freedom, pre-configured protocols, and, usually, they are expensive. In order to overcome these limits, we developed a robotic platform: Dynamic Oriented Rehabilitative Integrated System (DORIS). We aimed at realizing a versatile solution that can be applied both for research purposes but also for personalizing the training of equilibrium and gait. We reached these goals by means of a Stewart platform that was realized with linear actuators and a supporting plate. Each actuator is provided by an ad hoc built monoaxial load cell. Position control allows a large range of movements and load cells measure the reactive force applied by the subject. Transmission Control Protocol/Internet Protocol (TCP/IP) guarantees the communication between the platform and other systems. We integrated DORIS with a motion analysis system, an electromyography (EMG) system, and a virtual reality environment (VR). This integration and the custom design of the platform offer the opportunity to manipulate the available information of the subject under analysis, which uses visual, vestibular, and plantar feet pressure inputs. The full access to the human movements and to the dynamic interaction is a further benefit for the identification of innovative solutions for research and physical rehabilitation purposes in a field that is widely investigated but still open. Full article
(This article belongs to the Special Issue Multi-Sensor-Based Intelligent Systems for Physical Rehabilitation)
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Open AccessArticle
Workshop, Cost-Effective and Streamlined Fabrications of Re-Usable World-To-Chip Connectors for Handling Sample of Limited Volume and for Assembling Chip Array
Sensors 2018, 18(12), 4223; https://doi.org/10.3390/s18124223 - 01 Dec 2018
Abstract
The world-to-chip interface is an essential yet intriguing part of making and employing microfluidic devices. A user-friendly connector could be expensive or difficult to make. We fabricated two ports of microfluidic chips with easily available materials including Teflon blocks, double adhesive films, coverslips, [...] Read more.
The world-to-chip interface is an essential yet intriguing part of making and employing microfluidic devices. A user-friendly connector could be expensive or difficult to make. We fabricated two ports of microfluidic chips with easily available materials including Teflon blocks, double adhesive films, coverslips, and transparency films. By using a mini grinder, coverslips were drilled to form small holes for the fluid passages between port and chip. Except for the double adhesive films, the resultant ports are durable and re-useable. The DK1 port, contains a mini three-way switch which allows users to handle fluid by a tube-connected pump, or by a manual pipette for the sample of trace amount. The other port, the DK2 port, provides secured tube-connections. Importantly, we invented a bridge made of craft cutter-treated transparency films and double adhesive films to mediate liquid flow between DK2 port and chip. With the use of a bridge, users do not need to design new ports for new chips. Also, individual chips could be linked by a bridge to form a chip array. We successfully applied DK1 port on a microfluidic chip where green fluorescent protein was immobilized. We used DK2 port on an array of fish chips where the embryos of zebra fish developed. Full article
(This article belongs to the Special Issue Multi-Sensor-Based Intelligent Systems for Physical Rehabilitation)
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