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Khan MA, Fares H, Ghayvat H, Brunner IC, Puthusserypady S, Razavi B, Lansberg M, Poon A, Meador KJ. A systematic review on functional electrical stimulation based rehabilitation systems for upper limb post-stroke recovery. Front Neurol 2023; 14:1272992. [PMID: 38145118 PMCID: PMC10739305 DOI: 10.3389/fneur.2023.1272992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 11/20/2023] [Indexed: 12/26/2023] Open
Abstract
Background Stroke is one of the most common neurological conditions that often leads to upper limb motor impairments, significantly affecting individuals' quality of life. Rehabilitation strategies are crucial in facilitating post-stroke recovery and improving functional independence. Functional Electrical Stimulation (FES) systems have emerged as promising upper limb rehabilitation tools, offering innovative neuromuscular reeducation approaches. Objective The main objective of this paper is to provide a comprehensive systematic review of the start-of-the-art functional electrical stimulation (FES) systems for upper limb neurorehabilitation in post-stroke therapy. More specifically, this paper aims to review different types of FES systems, their feasibility testing, or randomized control trials (RCT) studies. Methods The FES systems classification is based on the involvement of patient feedback within the FES control, which mainly includes "Open-Loop FES Systems" (manually controlled) and "Closed-Loop FES Systems" (brain-computer interface-BCI and electromyography-EMG controlled). Thus, valuable insights are presented into the technological advantages and effectiveness of Manual FES, EEG-FES, and EMG-FES systems. Results and discussion The review analyzed 25 studies and found that the use of FES-based rehabilitation systems resulted in favorable outcomes for the stroke recovery of upper limb functional movements, as measured by the FMA (Fugl-Meyer Assessment) (Manually controlled FES: mean difference = 5.6, 95% CI (3.77, 7.5), P < 0.001; BCI-controlled FES: mean difference = 5.37, 95% CI (4.2, 6.6), P < 0.001; EMG-controlled FES: mean difference = 14.14, 95% CI (11.72, 16.6), P < 0.001) and ARAT (Action Research Arm Test) (EMG-controlled FES: mean difference = 11.9, 95% CI (8.8, 14.9), P < 0.001) scores. Furthermore, the shortcomings, clinical considerations, comparison to non-FES systems, design improvements, and possible future implications are also discussed for improving stroke rehabilitation systems and advancing post-stroke recovery. Thus, summarizing the existing literature, this review paper can help researchers identify areas for further investigation. This can lead to formulating research questions and developing new studies aimed at improving FES systems and their outcomes in upper limb rehabilitation.
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Affiliation(s)
- Muhammad Ahmed Khan
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA, United States
- Department of Electrical Engineering, Stanford University, Palo Alto, CA, United States
- Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Hoda Fares
- Department of Electrical, Electronic, Telecommunication Engineering and Naval Architecture (DITEN), University of Genoa, Genoa, Italy
| | - Hemant Ghayvat
- Department of Computer Science, Linnaeus University, Växjö, Sweden
| | | | | | - Babak Razavi
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA, United States
| | - Maarten Lansberg
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA, United States
| | - Ada Poon
- Department of Electrical Engineering, Stanford University, Palo Alto, CA, United States
| | - Kimford Jay Meador
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA, United States
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Remsik AB, van Kan PLE, Gloe S, Gjini K, Williams L, Nair V, Caldera K, Williams JC, Prabhakaran V. BCI-FES With Multimodal Feedback for Motor Recovery Poststroke. Front Hum Neurosci 2022; 16:725715. [PMID: 35874158 PMCID: PMC9296822 DOI: 10.3389/fnhum.2022.725715] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 05/26/2022] [Indexed: 01/31/2023] Open
Abstract
An increasing number of research teams are investigating the efficacy of brain-computer interface (BCI)-mediated interventions for promoting motor recovery following stroke. A growing body of evidence suggests that of the various BCI designs, most effective are those that deliver functional electrical stimulation (FES) of upper extremity (UE) muscles contingent on movement intent. More specifically, BCI-FES interventions utilize algorithms that isolate motor signals-user-generated intent-to-move neural activity recorded from cerebral cortical motor areas-to drive electrical stimulation of individual muscles or muscle synergies. BCI-FES interventions aim to recover sensorimotor function of an impaired extremity by facilitating and/or inducing long-term motor learning-related neuroplastic changes in appropriate control circuitry. We developed a non-invasive, electroencephalogram (EEG)-based BCI-FES system that delivers closed-loop neural activity-triggered electrical stimulation of targeted distal muscles while providing the user with multimodal sensory feedback. This BCI-FES system consists of three components: (1) EEG acquisition and signal processing to extract real-time volitional and task-dependent neural command signals from cerebral cortical motor areas, (2) FES of muscles of the impaired hand contingent on the motor cortical neural command signals, and (3) multimodal sensory feedback associated with performance of the behavioral task, including visual information, linked activation of somatosensory afferents through intact sensorimotor circuits, and electro-tactile stimulation of the tongue. In this report, we describe device parameters and intervention protocols of our BCI-FES system which, combined with standard physical rehabilitation approaches, has proven efficacious in treating UE motor impairment in stroke survivors, regardless of level of impairment and chronicity.
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Affiliation(s)
- Alexander B. Remsik
- Department of Radiology, University of Wisconsin–Madison, Madison, WI, United States
- School of Medicine and Public Health, Institute for Clinical and Translational Research, University of Wisconsin–Madison, Madison, WI, United States
- Department of Kinesiology, University of Wisconsin–Madison, Madison, WI, United States
| | - Peter L. E. van Kan
- Department of Kinesiology, University of Wisconsin–Madison, Madison, WI, United States
- Neuroscience Training Program, University of Wisconsin–Madison, Madison, WI, United States
| | - Shawna Gloe
- Department of Radiology, University of Wisconsin–Madison, Madison, WI, United States
| | - Klevest Gjini
- Department of Radiology, University of Wisconsin–Madison, Madison, WI, United States
- Department of Neurology, University of Wisconsin–Madison, Madison, WI, United States
| | - Leroy Williams
- Department of Radiology, University of Wisconsin–Madison, Madison, WI, United States
- Department of Educational Psychology, University of Wisconsin–Madison, Madison, WI, United States
| | - Veena Nair
- Department of Radiology, University of Wisconsin–Madison, Madison, WI, United States
| | - Kristin Caldera
- Department of Orthopedics and Rehabilitation, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, United States
| | - Justin C. Williams
- Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, WI, United States
- Department of Neurological Surgery, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, United States
| | - Vivek Prabhakaran
- Department of Radiology, University of Wisconsin–Madison, Madison, WI, United States
- Neuroscience Training Program, University of Wisconsin–Madison, Madison, WI, United States
- Department of Neurology, University of Wisconsin–Madison, Madison, WI, United States
- Department of Psychiatry, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, United States
- Medical Scientist Training Program, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, United States
- Department of Psychology, University of Wisconsin–Madison, Madison, WI, United States
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Mercado-Gutierrez JA, Dominguez R, Hernandez-Popo I, Quinzaños-Fresnedo J, Vera-Hernandez A, Leija-Salas L, Gutierrez-Martinez J. A Flexible Pulse Generator Based on a Field Programmable Gate Array Architecture for Functional Electrical Stimulation. Front Neurosci 2022; 15:702781. [PMID: 35126033 PMCID: PMC8814338 DOI: 10.3389/fnins.2021.702781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 12/09/2021] [Indexed: 11/15/2022] Open
Abstract
Non-invasive Functional Electrical Stimulation (FES) is a technique applied for motor rehabilitation of patients with central nervous system injury. This technique requires programmable multichannel systems to configure the stimulation parameters (amplitude, frequency, and pulse width). Most FES systems are based on microcontrollers with fixed architecture; this limits the control of the parameters and the scaling to multiple channels. Although field programmable gate arrays (FPGA) have been used in FES systems as alternative to microcontrollers, most of them focus on signal acquisition, processing, or communication functions, or are for invasive stimulation. A few FES systems report using FPGAs for parameter configuration and pulse generation in non-invasive FES. However, generally they limit the value of the frequency or amplitude parameters to enable multichannel operation. This restricts free selection of parameters and implementation of modulation patterns, previously reported to delay FES-induced muscle fatigue. To overcome those limitations, this paper presents a proof-of-concept (technology readiness level three-TRL 3) regarding the technical feasibility and potential use of an FPGA-based pulse generator for non-invasive FES applications (PG-nFES). The main aims were: (1) the development of a flexible pulse generator for FES applications and (2) to perform a proof-of-concept of the system, comprising: electrical characterization of the stimulation parameters, and verification of its potential for upper limb FES applications. Biphasic stimulation pulses with high linearity (r2 > 0.9998) and repeatability (>0.81) were achieved by combining the PG-nFES with a current-controlled output stage. Average percentage error in the characterizations was under 3% for amplitude (1–48 mA) and pulse width (20–400 μs), and 0% for frequency (10–150 Hz). A six-channel version of the PG-nFES was implemented to demonstrate the scalability feature. The independence of parameters was tested with three patterns of co-modulation of two parameters. Moreover, two complete FES channels were implemented and the claimed features of the PG-nFES were verified by performing upper limb functional movements involving the hand and the arm. Finally, the system enabled implementation of a stimulation pattern with co-modulation of frequency and pulse width, applied successfully for efficient elbow during repetitions of a functional movement.
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Affiliation(s)
- Jorge A. Mercado-Gutierrez
- Departamento de Ingeniería Eléctrica, Sección Bioelectrónica, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Mexico City, Mexico
- División de Investigación en Ingeniería Médica, Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City, Mexico
| | - Ricardo Dominguez
- Departamento de Ingeniería Eléctrica, Universidad Autónoma Metropolitana — Iztapalapa, Mexico City, Mexico
| | - Ignacio Hernandez-Popo
- CONACYT — Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City, Mexico
| | - Jimena Quinzaños-Fresnedo
- División de Rehabilitación Neurológica, Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City, Mexico
| | - Arturo Vera-Hernandez
- Departamento de Ingeniería Eléctrica, Sección Bioelectrónica, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Mexico City, Mexico
| | - Lorenzo Leija-Salas
- Departamento de Ingeniería Eléctrica, Sección Bioelectrónica, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Mexico City, Mexico
| | - Josefina Gutierrez-Martinez
- División de Investigación en Ingeniería Médica, Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City, Mexico
- *Correspondence: Josefina Gutierrez-Martinez,
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Camacho-Zavala JK, Perez-Medina AL, Mercado-Gutierrez JA, Gutierrez MI, Gutierrez-Martinez J, Aguirre-Güemez AV, Quinzaños-Fresnedo J, Perez-Orive J. Personalized protocol and scoring scale for functional electrical stimulation of the hand: A pilot feasibility study. Technol Health Care 2022; 30:51-63. [PMID: 34397438 DOI: 10.3233/thc-213016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
BACKGROUND Complex personalized Functional Electrical Stimulation (FES) protocols for calibrating parameters and electrode positioning have been proposed, most being time-consuming or technically cumbersome for clinical settings. Therefore, there is a need for new personalized FES protocols that generate comfortable, functional hand movements, while being feasible for clinical translation. OBJECTIVE To develop a personalized FES protocol, comprising electrode placement and parameter selection, to generate hand opening (HO), power grasp (PW) and precision grip (PG) movements, and compare in a pilot feasibility study its performance to a non-personalized protocol based on standard FES guidelines. METHODS Two FES protocols, one personalized (P1) and one non-personalized (P2), were used to produce hand movements in twenty-three healthy participants. FES-induced movements were assessed with a new scoring scale which comprises items for selectivity, functionality, and comfort. RESULTS Higher FES-HSS scores were obtained with P1 for all movements: HO (p= 0.00013), PW (p= 0.00007), PG (p= 0.00460). Electrode placement time was significantly shorter for P2 (p= 0.00003). Comfort scores were similar for both protocols. CONCLUSIONS The personalized protocol for electrode placement and parameter selection enabled functional FES-induced hand movements and presented advantages over a non-personalized protocol. This protocol warrants further investigation to confirm its suitability for developing upper-limb rehabilitation interventions with clinical translational potential.
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Affiliation(s)
- Jessica K Camacho-Zavala
- Facultad de Ingeniería, Universidad Nacional Autónoma de México, Cd. de México, México
- Facultad de Ingeniería, Universidad Nacional Autónoma de México, Cd. de México, México
| | - Ana L Perez-Medina
- Facultad de Ingeniería, Universidad Nacional Autónoma de México, Cd. de México, México
- Facultad de Ingeniería, Universidad Nacional Autónoma de México, Cd. de México, México
| | - Jorge A Mercado-Gutierrez
- División de Investigación en Ingeniería Médica, Instituto Nacional de Rehabilitación "Luis Guillermo Ibarra Ibarra", Cd. de México, México
| | - Mario I Gutierrez
- CONACYT-Instituto Nacional de Rehabilitación "Luis Guillermo Ibarra Ibarra", Cd. de México, México
| | - Josefina Gutierrez-Martinez
- División de Investigación en Ingeniería Médica, Instituto Nacional de Rehabilitación "Luis Guillermo Ibarra Ibarra", Cd. de México, México
| | - A Valeria Aguirre-Güemez
- División de Rehabilitación Neurológica, Instituto Nacional de Rehabilitación "Luis Guillermo Ibarra Ibarra", Cd. de México, México
| | - Jimena Quinzaños-Fresnedo
- División de Rehabilitación Neurológica, Instituto Nacional de Rehabilitación "Luis Guillermo Ibarra Ibarra", Cd. de México, México
| | - Javier Perez-Orive
- Facultad de Ingeniería, Universidad Nacional Autónoma de México, Cd. de México, México
- División de Neurociencias, Instituto Nacional de Rehabilitación "Luis Guillermo Ibarra Ibarra", Cd. de México, México
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Khan MA, Saibene M, Das R, Brunner IC, Puthusserypady S. Emergence of flexible technology in developing advanced systems for post-stroke rehabilitation: a comprehensive review. J Neural Eng 2021; 18. [PMID: 34736239 DOI: 10.1088/1741-2552/ac36aa] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Accepted: 11/04/2021] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Stroke is one of the most common neural disorders, which causes physical disabilities and motor impairments among its survivors. Several technologies have been developed for providing stroke rehabilitation and to assist the survivors in performing their daily life activities. Currently, the use of flexible technology (FT) for stroke rehabilitation systems is on a rise that allows the development of more compact and lightweight wearable systems, which stroke survivors can easily use for long-term activities. APPROACH For stroke applications, FT mainly includes the "flexible/stretchable electronics", "e-textile (electronic textile)" and "soft robotics". Thus, a thorough literature review has been performed to report the practical implementation of FT for post-stroke application. MAIN RESULTS In this review, the highlights of the advancement of FT in stroke rehabilitation systems are dealt with. Such systems mainly involve the "biosignal acquisition unit", "rehabilitation devices" and "assistive systems". In terms of biosignals acquisition, electroencephalography (EEG) and electromyography (EMG) are comprehensively described. For rehabilitation/assistive systems, the application of functional electrical stimulation (FES) and robotics units (exoskeleton, orthosis, etc.) have been explained. SIGNIFICANCE This is the first review article that compiles the different studies regarding flexible technology based post-stroke systems. Furthermore, the technological advantages, limitations, and possible future implications are also discussed to help improve and advance the flexible systems for the betterment of the stroke community.
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Affiliation(s)
- Muhammad Ahmed Khan
- Technical University of Denmark, Ørsteds Plads Building 345C, Room 215, Lyngby, 2800, DENMARK
| | - Matteo Saibene
- Technical University of Denmark, Ørsteds Plads, Building 345C, Lyngby, 2800, DENMARK
| | - Rig Das
- Technical University of Denmark, Ørsteds Plads Building 345C, Room 214, Lyngby, 2800, DENMARK
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Naros G, Lehnertz T, Leão MT, Ziemann U, Gharabaghi A. Brain State-dependent Gain Modulation of Corticospinal Output in the Active Motor System. Cereb Cortex 2021; 30:371-381. [PMID: 31204431 DOI: 10.1093/cercor/bhz093] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Revised: 03/18/2019] [Accepted: 04/10/2019] [Indexed: 01/17/2023] Open
Abstract
The communication through coherence hypothesis suggests that only coherently oscillating neuronal groups can interact effectively and predicts an intrinsic response modulation along the oscillatory rhythm. For the motor cortex (MC) at rest, the oscillatory cycle has been shown to determine the brain's responsiveness to external stimuli. For the active MC, however, the demonstration of such a phase-specific modulation of corticospinal excitability (CSE) along the rhythm cycle is still missing. Motor evoked potentials in response to transcranial magnetic stimulation (TMS) over the MC were used to probe the effect of cortical oscillations on CSE during several motor conditions. A brain-machine interface (BMI) with a robotic hand orthosis allowed investigating effects of cortical activity on CSE without the confounding effects of voluntary muscle activation. Only this BMI approach (and not active or passive hand opening alone) revealed a frequency- and phase-specific cortical modulation of CSE by sensorimotor beta-band activity that peaked once per oscillatory cycle and was independent of muscle activity. The active MC follows an intrinsic response modulation in accordance with the communication through coherence hypothesis. Furthermore, the BMI approach may facilitate and strengthen effective corticospinal communication in a therapeutic context, for example, when voluntary hand opening is no longer possible after stroke.
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Affiliation(s)
- Georgios Naros
- Division of Functional and Restorative Neurosurgery, and Tuebingen NeuroCampus, Eberhard Karls University Tuebingen, 72076 Tuebingen, Germany
| | - Tobias Lehnertz
- Division of Functional and Restorative Neurosurgery, and Tuebingen NeuroCampus, Eberhard Karls University Tuebingen, 72076 Tuebingen, Germany
| | - Maria Teresa Leão
- Division of Functional and Restorative Neurosurgery, and Tuebingen NeuroCampus, Eberhard Karls University Tuebingen, 72076 Tuebingen, Germany
| | - Ulf Ziemann
- Department of Neurology and Stroke, and Hertie Institute for Clinical Brain Research, Eberhard Karls University Tuebingen, 72076 Tuebingen, Germany
| | - Alireza Gharabaghi
- Division of Functional and Restorative Neurosurgery, and Tuebingen NeuroCampus, Eberhard Karls University Tuebingen, 72076 Tuebingen, Germany
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Saha S, Mamun KA, Ahmed K, Mostafa R, Naik GR, Darvishi S, Khandoker AH, Baumert M. Progress in Brain Computer Interface: Challenges and Opportunities. Front Syst Neurosci 2021; 15:578875. [PMID: 33716680 PMCID: PMC7947348 DOI: 10.3389/fnsys.2021.578875] [Citation(s) in RCA: 82] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 01/06/2021] [Indexed: 12/13/2022] Open
Abstract
Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such as rehabilitation, affective computing, robotics, gaming, and neuroscience. Significant research efforts on a global scale have delivered common platforms for technology standardization and help tackle highly complex and non-linear brain dynamics and related feature extraction and classification challenges. Time-variant psycho-neurophysiological fluctuations and their impact on brain signals impose another challenge for BCI researchers to transform the technology from laboratory experiments to plug-and-play daily life. This review summarizes state-of-the-art progress in the BCI field over the last decades and highlights critical challenges.
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Affiliation(s)
- Simanto Saha
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia
- Department of Electrical and Electronic Engineering, United International University, Dhaka, Bangladesh
| | - Khondaker A. Mamun
- Advanced Intelligent Multidisciplinary Systems (AIMS) Lab, Department of Computer Science and Engineering, United International University, Dhaka, Bangladesh
| | - Khawza Ahmed
- Department of Electrical and Electronic Engineering, United International University, Dhaka, Bangladesh
| | - Raqibul Mostafa
- Department of Electrical and Electronic Engineering, United International University, Dhaka, Bangladesh
| | - Ganesh R. Naik
- Adelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
| | - Sam Darvishi
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia
| | - Ahsan H. Khandoker
- Healthcare Engineering Innovation Center, Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Mathias Baumert
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia
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Sauder NR, Meyer AJ, Allen JL, Ting LH, Kesar TM, Fregly BJ. Computational Design of FastFES Treatment to Improve Propulsive Force Symmetry During Post-stroke Gait: A Feasibility Study. Front Neurorobot 2019; 13:80. [PMID: 31632261 PMCID: PMC6779709 DOI: 10.3389/fnbot.2019.00080] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Accepted: 09/10/2019] [Indexed: 12/20/2022] Open
Abstract
Stroke is a leading cause of long-term disability worldwide and often impairs walking ability. To improve recovery of walking function post-stroke, researchers have investigated the use of treatments such as fast functional electrical stimulation (FastFES). During FastFES treatments, individuals post-stroke walk on a treadmill at their fastest comfortable speed while electrical stimulation is delivered to two muscles of the paretic ankle, ideally to improve paretic leg propulsion and toe clearance. However, muscle selection and stimulation timing are currently standardized based on clinical intuition and a one-size-fits-all approach, which may explain in part why some patients respond to FastFES training while others do not. This study explores how personalized neuromusculoskeletal models could potentially be used to enable individual-specific selection of target muscles and stimulation timing to address unique functional limitations of individual patients post-stroke. Treadmill gait data, including EMG, surface marker positions, and ground reactions, were collected from an individual post-stroke who was a non-responder to FastFES treatment. The patient's gait data were used to personalize key aspects of a full-body neuromusculoskeletal walking model, including lower-body joint functional axes, lower-body muscle force generating properties, deformable foot-ground contact properties, and paretic and non-paretic leg neural control properties. The personalized model was utilized within a direct collocation optimal control framework to reproduce the patient's unstimulated treadmill gait data (verification problem) and to generate three stimulated walking predictions that sought to minimize inter-limb propulsive force asymmetry (prediction problems). The three predictions used: (1) Standard muscle selection (gastrocnemius and tibialis anterior) with standard stimulation timing, (2) Standard muscle selection with optimized stimulation timing, and (3) Optimized muscle selection (soleus and semimembranosus) with optimized stimulation timing. Relative to unstimulated walking, the optimal control problems predicted a 41% reduction in propulsive force asymmetry for scenario (1), a 45% reduction for scenario (2), and a 64% reduction for scenario (3), suggesting that non-standard muscle selection may be superior for this patient. Despite these predicted improvements, kinematic symmetry was not noticeably improved for any of the walking predictions. These results suggest that personalized neuromusculoskeletal models may be able to predict personalized FastFES training prescriptions that could improve propulsive force symmetry, though inclusion of kinematic requirements would be necessary to improve kinematic symmetry as well.
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Affiliation(s)
- Nathan R Sauder
- Computational Biomechanics Laboratory, Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, United States
| | - Andrew J Meyer
- Computational Biomechanics Laboratory, Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, United States
| | - Jessica L Allen
- Neuromechanics Laboratory, Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States
| | - Lena H Ting
- Neuromechanics Laboratory, Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States.,Motion Analysis Laboratory, Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, GA, United States
| | - Trisha M Kesar
- Motion Analysis Laboratory, Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, GA, United States
| | - Benjamin J Fregly
- Rice Computational Neuromechanics Laboratory, Department of Mechanical Engineering, Rice University, Houston, TX, United States
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Zheng Y, Hu X. Elicited Finger and Wrist Extension Through Transcutaneous Radial Nerve Stimulation. IEEE Trans Neural Syst Rehabil Eng 2019; 27:1875-1882. [DOI: 10.1109/tnsre.2019.2930669] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Salchow-Hömmen C, Jankowski N, Valtin M, Schönijahn L, Böttcher S, Dähne F, Schauer T. User-centered practicability analysis of two identification strategies in electrode arrays for FES induced hand motion in early stroke rehabilitation. J Neuroeng Rehabil 2018; 15:123. [PMID: 30594257 PMCID: PMC6310929 DOI: 10.1186/s12984-018-0460-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Accepted: 11/12/2018] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Surface electrode arrays have become popular in the application of functional electrical stimulation (FES) on the forearm. Arrays consist of multiple, small elements, which can be activated separately or in groups, forming virtual electrodes (VEs). As technology progress yields rising numbers of possible elements, an effective search strategy for suitable VEs in electrode arrays is of increasing importance. Current methods can be time-consuming, lack user integration, and miss an evaluation regarding clinical acceptance and practicability. METHODS Two array identification procedures with different levels of user integration-a semi-automatic and a fully automatic approach-are evaluated. The semi-automatic method allows health professionals to continuously modify VEs via a touchscreen while the stimulation intensities are automatically controlled to maintain sufficient wrist extension. The automatic approach evaluates stimulation responses of various VEs for different intensities using a cost function and joint-angles recordings. Both procedures are compared in a clinical setup with five sub-acute stroke patients with moderate hand disabilities. The task was to find suitable VEs in two arrays with 59 elements in total to generate hand opening and closing for a grasp-and-release task. Practicability and acceptance by patients and health professionals were investigated using questionnaires and interviews. RESULTS Both identification methods yield suitable VEs for hand opening and closing in patients who could tolerate the stimulation. However, the resulting VEs differed for both approaches. The average time for a complete search was 25% faster for the semi-automatic approach (semi-automatic: 7.3min, automatic: 10.5min). User acceptance was high for both methods, while no clear preference could be identified. CONCLUSIONS The semi-automatic approach should be preferred as the search strategy in arrays on the forearm. The observed faster search duration will further reduce when applying the system repeatedly on a patient as only small position adjustments for VEs are required. However, the setup time will significantly increase for generation of various grasp types and adaptation to different arm postures. We recommend different levels of user integration in FES systems such that the search strategy can be chosen based on the users' preferences and application scenario.
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Affiliation(s)
| | - Natalie Jankowski
- Institut für Rehabilitationswissenschaften, Humboldt Universität zu Berlin, Unter den Linden 6, Berlin, 10099 Germany
| | - Markus Valtin
- Control Systems Group, Technische Universität Berlin, Einsteinufer 17, Berlin, 10587 Germany
| | - Laura Schönijahn
- Institut für Rehabilitationswissenschaften, Humboldt Universität zu Berlin, Unter den Linden 6, Berlin, 10099 Germany
| | - Sebastian Böttcher
- Klinik für Neurologie mit Stroke Unit und Frührehabilitation, Unfallkrankenhaus Berlin, Warener Str. 7, Berlin, 12683 Germany
| | - Frank Dähne
- Klinik für Neurologie mit Stroke Unit und Frührehabilitation, Unfallkrankenhaus Berlin, Warener Str. 7, Berlin, 12683 Germany
| | - Thomas Schauer
- Control Systems Group, Technische Universität Berlin, Einsteinufer 17, Berlin, 10587 Germany
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11
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sEMG Signal Acquisition Strategy towards Hand FES Control. JOURNAL OF HEALTHCARE ENGINEERING 2018; 2018:2350834. [PMID: 29732046 PMCID: PMC5872608 DOI: 10.1155/2018/2350834] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Revised: 12/01/2017] [Accepted: 12/27/2017] [Indexed: 12/23/2022]
Abstract
Due to damage of the nervous system, patients experience impediments in their daily life: severe fatigue, tremor or impaired hand dexterity, hemiparesis, or hemiplegia. Surface electromyography (sEMG) signal analysis is used to identify motion; however, standardization of electrode placement and classification of sEMG patterns are major challenges. This paper describes a technique used to acquire sEMG signals for five hand motion patterns from six able-bodied subjects using an array of recording and stimulation electrodes placed on the forearm and its effects over functional electrical stimulation (FES) and volitional sEMG combinations, in order to eventually control a sEMG-driven FES neuroprosthesis for upper limb rehabilitation. A two-part protocol was performed. First, personalized templates to place eight sEMG bipolar channels were designed; with these data, a universal template, called forearm electrode set (FELT), was built. Second, volitional and evoked movements were recorded during FES application. 95% classification accuracy was achieved using two sessions per movement. With the FELT, it was possible to perform FES and sEMG recordings simultaneously. Also, it was possible to extract the volitional and evoked sEMG from the raw signal, which is highly important for closed-loop FES control.
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12
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Abouelseoud G, Abouelseoud Y, Shoukry A, Ismail N, Mekky J. A Mixed Integer Linear Programming Approach to Electrical Stimulation Optimization Problems. IEEE Trans Neural Syst Rehabil Eng 2018; 26:527-537. [PMID: 29432118 DOI: 10.1109/tnsre.2018.2789380] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Electrical stimulation optimization is a challenging problem. Even when a single region is targeted for excitation, the problem remains a constrained multi-objective optimization problem. The constrained nature of the problem results from safety concerns while its multi-objectives originate from the requirement that non-targeted regions should remain unaffected. In this paper, we propose a mixed integer linear programming formulation that can successfully address the challenges facing this problem. Moreover, the proposed framework can conclusively check the feasibility of the stimulation goals. This helps researchers to avoid wasting time trying to achieve goals that are impossible under a chosen stimulation setup. The superiority of the proposed framework over alternative methods is demonstrated through simulation examples.
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13
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Electrode placement on the forearm for selective stimulation of finger extension/flexion. PLoS One 2018; 13:e0190936. [PMID: 29324829 PMCID: PMC5764314 DOI: 10.1371/journal.pone.0190936] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2017] [Accepted: 12/22/2017] [Indexed: 12/17/2022] Open
Abstract
It is still challenging to achieve a complex grasp or fine finger control by using surface functional electrical stimulation (FES), which usually requires a precise electrode configuration under laboratory or clinical settings. The goals of this study are as follows: 1) to study the possibility of selectively activating individual fingers; 2) to investigate whether the current activation threshold and selective range of individual fingers are affected by two factors: changes in the electrode position and forearm rotation (pronation, neutral and supination); and 3) to explore a theoretical model for guidance of the electrode placement used for selective activation of individual fingers. A coordinate system with more than 400 grid points was established over the forearm skin surface. A searching procedure was used to traverse all grid points to identify the stimulation points for finger extension/flexion by applying monophasic stimulation pulses. Some of the stimulation points for finger extension and flexion were selected and tested in their respective two different forearm postures according to the number and the type of the activated fingers and the strength of finger action response to the electrical stimulation at the stimulation point. The activation thresholds and current ranges of the selectively activated finger at each stimulation point were determined by visual analysis. The stimulation points were divided into three groups (“Low”, “Medium” and “High”) according to the thresholds of the 1st activated fingers. The angles produced by the selectively activated finger within selective current ranges were measured and analyzed. Selective stimulation of extension/flexion is possible for most fingers. Small changes in electrode position and forearm rotation have no significant effect on the threshold amplitude and the current range for the selective activation of most fingers (p > 0.05). The current range is the largest (more than 2 mA) for selective activation of the thumb, followed by those for the index, ring, middle and little fingers. The stimulation points in the “Low” group for all five fingers lead to noticeable finger angles at low current intensity, especially for the index, middle, and ring fingers. The slopes of the finger angle variation in the “Low” group for digits 2~4 are inversely proportional to the current intensity, whereas the slopes of the finger angle variation in other groups and in all groups for the thumb and little finger are proportional to the current intensity. It is possible to selectively activate the extension/flexion of most fingers by stimulating the forearm muscles. The physiological characteristics of each finger should be considered when placing the negative electrode for selective stimulation of individual fingers. The electrode placement used for the selective activation of individual fingers should not be confined to the location with the lowest activation threshold.
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14
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Malešević J, Dedijer Dujović S, Savić AM, Konstantinović L, Vidaković A, Bijelić G, Malešević N, Keller T. A decision support system for electrode shaping in multi-pad FES foot drop correction. J Neuroeng Rehabil 2017; 14:66. [PMID: 28673311 PMCID: PMC5496361 DOI: 10.1186/s12984-017-0275-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2016] [Accepted: 06/18/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Functional electrical stimulation (FES) can be applied as an assistive and therapeutic aid in the rehabilitation of foot drop. Transcutaneous multi-pad electrodes can increase the selectivity of stimulation; however, shaping the stimulation electrode becomes increasingly complex with an increasing number of possible stimulation sites. We described and tested a novel decision support system (DSS) to facilitate the process of multi-pad stimulation electrode shaping. The DSS is part of a system for drop foot treatment that comprises a custom-designed multi-pad electrode, an electrical stimulator, and an inertial measurement unit. METHODS The system was tested in ten stroke survivors (3-96 months post stroke) with foot drop over 20 daily sessions. The DSS output suggested stimulation pads and parameters based on muscle twitch responses to short stimulus trains. The DSS ranked combinations of pads and current amplitudes based on a novel measurement of the quality of the induced movement and classified them based on the movement direction (dorsiflexion, plantar flexion, eversion and inversion) of the paretic foot. The efficacy of the DSS in providing satisfactory pad-current amplitude choices for shaping the stimulation electrode was evaluated by trained clinicians. The range of paretic foot motion was used as a quality indicator for the chosen patterns. RESULTS The results suggest that the DSS output was highly effective in creating optimized FES patterns. The position and number of pads included showed pronounced inter-patient and inter-session variability; however, zones for inducing dorsiflexion and plantar flexion within the multi-pad electrode were clearly separated. The range of motion achieved with FES was significantly greater than the corresponding active range of motion (p < 0.05) during the first three weeks of therapy. CONCLUSIONS The proposed DSS in combination with a custom multi-pad electrode design covering the branches of peroneal and tibial nerves proved to be an effective tool for producing both the dorsiflexion and plantar flexion of a paretic foot. The results support the use of multi-pad electrode technology in combination with automatic electrode shaping algorithms for the rehabilitation of foot drop. TRIAL REGISTRATION This study was registered at the Current Controlled Trials website with ClinicalTrials.gov ID NCT02729636 on March 29, 2016.
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Affiliation(s)
- Jovana Malešević
- Tecnalia Serbia Ltd., Belgrade, Serbia. .,University of Belgrade, Belgrade, Serbia.
| | - Suzana Dedijer Dujović
- University of Belgrade, Belgrade, Serbia.,Clinic for Rehabilitation "Dr Miroslav Zotović", Belgrade, Serbia
| | - Andrej M Savić
- Tecnalia Serbia Ltd., Belgrade, Serbia.,University of Belgrade, School of Electrical Engineering, Belgrade, Serbia
| | - Ljubica Konstantinović
- Clinic for Rehabilitation "Dr Miroslav Zotović", Belgrade, Serbia.,University of Belgrade, Faculty of Medicine, Belgrade, Serbia
| | - Aleksandra Vidaković
- Clinic for Rehabilitation "Dr Miroslav Zotović", Belgrade, Serbia.,University of Belgrade, Faculty of Medicine, Belgrade, Serbia
| | - Goran Bijelić
- Tecnalia Research & Innovation - Health Division, Donostia-San Sebastián, Spain
| | - Nebojša Malešević
- University of Belgrade, School of Electrical Engineering, Belgrade, Serbia.,Department of Biomedical Engineering, Lund University, Lund, Sweden
| | - Thierry Keller
- Tecnalia Research & Innovation - Health Division, Donostia-San Sebastián, Spain
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Grimm F, Walter A, Spüler M, Naros G, Rosenstiel W, Gharabaghi A. Hybrid Neuroprosthesis for the Upper Limb: Combining Brain-Controlled Neuromuscular Stimulation with a Multi-Joint Arm Exoskeleton. Front Neurosci 2016; 10:367. [PMID: 27555805 PMCID: PMC4977295 DOI: 10.3389/fnins.2016.00367] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2016] [Accepted: 07/25/2016] [Indexed: 11/13/2022] Open
Abstract
Brain-machine interface-controlled (BMI) neurofeedback training aims to modulate cortical physiology and is applied during neurorehabilitation to increase the responsiveness of the brain to subsequent physiotherapy. In a parallel line of research, robotic exoskeletons are used in goal-oriented rehabilitation exercises for patients with severe motor impairment to extend their range of motion (ROM) and the intensity of training. Furthermore, neuromuscular electrical stimulation (NMES) is applied in neurologically impaired patients to restore muscle strength by closing the sensorimotor loop. In this proof-of-principle study, we explored an integrated approach for providing assistance as needed to amplify the task-related ROM and the movement-related brain modulation during rehabilitation exercises of severely impaired patients. For this purpose, we combined these three approaches (BMI, NMES, and exoskeleton) in an integrated neuroprosthesis and studied the feasibility of this device in seven severely affected chronic stroke patients who performed wrist flexion and extension exercises while receiving feedback via a virtual environment. They were assisted by a gravity-compensating, seven degree-of-freedom exoskeleton which was attached to the paretic arm. NMES was applied to the wrist extensor and flexor muscles during the exercises and was controlled by a hybrid BMI based on both sensorimotor cortical desynchronization (ERD) and electromyography (EMG) activity. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e., induced no overt support. The hybrid BMI controlled the stimulation significantly better than the offline analyzed ERD (p = 0.028) or EMG (p = 0.021) modality alone. Neuromuscular stimulation could be well integrated into the exoskeleton-based training and amplified both the task-related ROM (p = 0.009) and the movement-related brain modulation (p = 0.019). Combining a hybrid BMI with neuromuscular stimulation and antigravity assistance augments upper limb function and brain activity during rehabilitation exercises and may thus provide a novel restorative framework for severely affected stroke patients.
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Affiliation(s)
- Florian Grimm
- Division of Functional and Restorative Neurosurgery, Centre for Integrative Neuroscience, Eberhard Karls University Tuebingen Tuebingen, Germany
| | - Armin Walter
- Department of Computer Engineering, Wilhelm Schickard Institute for Computer Science, Eberhard Karls University Tuebingen Tuebingen, Germany
| | - Martin Spüler
- Department of Computer Engineering, Wilhelm Schickard Institute for Computer Science, Eberhard Karls University Tuebingen Tuebingen, Germany
| | - Georgios Naros
- Division of Functional and Restorative Neurosurgery, Centre for Integrative Neuroscience, Eberhard Karls University Tuebingen Tuebingen, Germany
| | - Wolfgang Rosenstiel
- Department of Computer Engineering, Wilhelm Schickard Institute for Computer Science, Eberhard Karls University Tuebingen Tuebingen, Germany
| | - Alireza Gharabaghi
- Division of Functional and Restorative Neurosurgery, Centre for Integrative Neuroscience, Eberhard Karls University Tuebingen Tuebingen, Germany
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