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Tian Y, Saradhi S, Bello E, Johnson MD, D’Eleuterio G, Popovic MR, Lankarany M. Model-based closed-loop control of thalamic deep brain stimulation. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 4:1356653. [PMID: 38650608 PMCID: PMC11033853 DOI: 10.3389/fnetp.2024.1356653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 03/18/2024] [Indexed: 04/25/2024]
Abstract
Introduction: Closed-loop control of deep brain stimulation (DBS) is beneficial for effective and automatic treatment of various neurological disorders like Parkinson's disease (PD) and essential tremor (ET). Manual (open-loop) DBS programming solely based on clinical observations relies on neurologists' expertise and patients' experience. Continuous stimulation in open-loop DBS may decrease battery life and cause side effects. On the contrary, a closed-loop DBS system uses a feedback biomarker/signal to track worsening (or improving) of patients' symptoms and offers several advantages compared to the open-loop DBS system. Existing closed-loop DBS control systems do not incorporate physiological mechanisms underlying DBS or symptoms, e.g., how DBS modulates dynamics of synaptic plasticity. Methods: In this work, we propose a computational framework for development of a model-based DBS controller where a neural model can describe the relationship between DBS and neural activity and a polynomial-based approximation can estimate the relationship between neural and behavioral activities. A controller is used in our model in a quasi-real-time manner to find DBS patterns that significantly reduce the worsening of symptoms. By using the proposed computational framework, these DBS patterns can be tested clinically by predicting the effect of DBS before delivering it to the patient. We applied this framework to the problem of finding optimal DBS frequencies for essential tremor given electromyography (EMG) recordings solely. Building on our recent network model of ventral intermediate nuclei (Vim), the main surgical target of the tremor, in response to DBS, we developed neural model simulation in which physiological mechanisms underlying Vim-DBS are linked to symptomatic changes in EMG signals. By using a proportional-integral-derivative (PID) controller, we showed that a closed-loop system can track EMG signals and adjust the stimulation frequency of Vim-DBS so that the power of EMG reaches a desired control target. Results and discussion: We demonstrated that the model-based DBS frequency aligns well with that used in clinical studies. Our model-based closed-loop system is adaptable to different control targets and can potentially be used for different diseases and personalized systems.
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Affiliation(s)
- Yupeng Tian
- Krembil Brain Institute—University Health Network, Toronto, ON, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
- KITE Research Institute, Toronto Rehabilitation Institute - University Health Network, Toronto, ON, Canada
| | - Srikar Saradhi
- Krembil Brain Institute—University Health Network, Toronto, ON, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
| | - Edward Bello
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Matthew D. Johnson
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States
| | | | - Milos R. Popovic
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
- KITE Research Institute, Toronto Rehabilitation Institute - University Health Network, Toronto, ON, Canada
- Center for Advancing Neurotechnological Innovation to Application, University Health Network and University of Toronto, Toronto, ON, Canada
| | - Milad Lankarany
- Krembil Brain Institute—University Health Network, Toronto, ON, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
- KITE Research Institute, Toronto Rehabilitation Institute - University Health Network, Toronto, ON, Canada
- Center for Advancing Neurotechnological Innovation to Application, University Health Network and University of Toronto, Toronto, ON, Canada
- Department of Physiology, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
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Smid A, Dominguez-Vega ZT, van Laar T, Oterdoom DLM, Absalom AR, van Egmond ME, Drost G, van Dijk JMC. Objective clinical registration of tremor, bradykinesia, and rigidity during awake stereotactic neurosurgery: a scoping review. Neurosurg Rev 2024; 47:81. [PMID: 38355824 PMCID: PMC10866747 DOI: 10.1007/s10143-024-02312-4] [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] [Received: 12/06/2023] [Revised: 01/19/2024] [Accepted: 01/28/2024] [Indexed: 02/16/2024]
Abstract
Tremor, bradykinesia, and rigidity are incapacitating motor symptoms that can be suppressed with stereotactic neurosurgical treatment like deep brain stimulation (DBS) and ablative surgery (e.g., thalamotomy, pallidotomy). Traditionally, clinicians rely on clinical rating scales for intraoperative evaluation of these motor symptoms during awake stereotactic neurosurgery. However, these clinical scales have a relatively high inter-rater variability and rely on experienced raters. Therefore, objective registration (e.g., using movement sensors) is a reasonable extension for intraoperative assessment of tremor, bradykinesia, and rigidity. The main goal of this scoping review is to provide an overview of electronic motor measurements during awake stereotactic neurosurgery. The protocol was based on the PRISMA extension for scoping reviews. After a systematic database search (PubMed, Embase, and Web of Science), articles were screened for relevance. Hundred-and-three articles were subject to detailed screening. Key clinical and technical information was extracted. The inclusion criteria encompassed use of electronic motor measurements during stereotactic neurosurgery performed under local anesthesia. Twenty-three articles were included. These studies had various objectives, including correlating sensor-based outcome measures to clinical scores, identifying optimal DBS electrode positions, and translating clinical assessments to objective assessments. The studies were highly heterogeneous in device choice, sensor location, measurement protocol, design, outcome measures, and data analysis. This review shows that intraoperative quantification of motor symptoms is still limited by variable signal analysis techniques and lacking standardized measurement protocols. However, electronic motor measurements can complement visual evaluations and provide objective confirmation of correct placement of the DBS electrode and/or lesioning. On the long term, this might benefit patient outcomes and provide reliable outcome measures in scientific research.
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Affiliation(s)
- Annemarie Smid
- Department of Neurosurgery, University Medical Center Groningen, University of Groningen, Hanzeplein 1 HPC AB71, 9713 GZ, Groningen, Netherlands.
| | - Zeus T Dominguez-Vega
- Department of Neurology, University Medical Center Groningen, University of Groningen, Hanzeplein 1 HPC AB71, 9713 GZ, Groningen, Netherlands
| | - Teus van Laar
- Department of Neurology, University Medical Center Groningen, University of Groningen, Hanzeplein 1 HPC AB71, 9713 GZ, Groningen, Netherlands
| | - D L Marinus Oterdoom
- Department of Neurosurgery, University Medical Center Groningen, University of Groningen, Hanzeplein 1 HPC AB71, 9713 GZ, Groningen, Netherlands
| | - Anthony R Absalom
- Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1 HPC AB71, 9713 GZ, Groningen, Netherlands
| | - Martje E van Egmond
- Department of Neurology, University Medical Center Groningen, University of Groningen, Hanzeplein 1 HPC AB71, 9713 GZ, Groningen, Netherlands
| | - Gea Drost
- Department of Neurosurgery, University Medical Center Groningen, University of Groningen, Hanzeplein 1 HPC AB71, 9713 GZ, Groningen, Netherlands
- Department of Neurology, University Medical Center Groningen, University of Groningen, Hanzeplein 1 HPC AB71, 9713 GZ, Groningen, Netherlands
| | - J Marc C van Dijk
- Department of Neurosurgery, University Medical Center Groningen, University of Groningen, Hanzeplein 1 HPC AB71, 9713 GZ, Groningen, Netherlands
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Kilinc B, Cetisli-Korkmaz N, Bir LS, Marangoz AD, Senol H. The quality of life in individuals with Parkinson's Disease: is it related to functionality and tremor severity? A cross-sectional study. Physiother Theory Pract 2023:1-10. [PMID: 37515776 DOI: 10.1080/09593985.2023.2236691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 07/10/2023] [Accepted: 07/10/2023] [Indexed: 07/31/2023]
Abstract
BACKGROUND Symptoms seen in Parkinson's Disease (PD) affect the quality of life (QoL) of individuals. OBJECTIVES This study aimed to examine the relationship of QoL with tremor severity and upper limb functionality in individuals with PD. METHODS Parkinson's Disease Quality of Life Questionnaire (PDQ-39) was used to examine the QoL of the participants, electromyography was used to measure the tremor amplitude, Nine-Hole Peg Test (NHPT) was used to evaluate the upper limb functionality and dynamometer was used to evaluate grip and pinch strength. Resting and postural tremor amplitudes were recorded from both sides of the hand and forearm. The relationship between QoL and other parameters was tested with Spearman Correlation Analysis. Mann-Whitney U test was used to compare individuals with and without tremor. RESULTS It was obtained that tremor amplitude was significantly related to: activities of daily living (rho = 0.597); emotional well-being (rho = 0.694); stigma (rho = 0.524); social support (rho = 0.595 and 0.559), and communication [rho = 0.532 (right forearm), 0.564 (left forearm), and 0.527 (right hand)] sub-parameters of PDQ-39 (p < .05). The relationship of the grip and pinch strength with the PDQ-39 sub-parameters was significant (p < .05), except for social support and communication. The relationship between NHPT and almost all parameters of PDQ-39 (p < .05), except bodily discomfort and social support, was significant. CONCLUSION It was concluded that future studies focusing on QoL could also consider tremor severity and grip strength as well as dexterity in individuals with PD.
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Affiliation(s)
- Buse Kilinc
- Institute of Health Sciences, Department of Physical Therapy and Rehabilitation, Pamukkale University, Denizli, Türkiye
| | | | - Levent Sinan Bir
- Faculty of Medicine, Department of Neurology, Pamukkale University, Denizli, Türkiye
| | - Ahmet Dogucem Marangoz
- Department of Geriatric Psychiatry and Psychotherapy, Klinikum Stuttgart, Stuttgart, Germany
| | - Hande Senol
- Faculty of Medicine, Department of Biostatistics, Pamukkale University, Denizli, Türkiye
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Ma R, Yin Z, Chen Y, Yuan T, An Q, Gan Y, Xu Y, Jiang Y, Du T, Yang A, Meng F, Zhu G, Zhang J. Sleep outcomes and related factors in Parkinson's disease after subthalamic deep brain electrode implantation: a retrospective cohort study. Ther Adv Neurol Disord 2023; 16:17562864231161163. [PMID: 37200769 PMCID: PMC10185976 DOI: 10.1177/17562864231161163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 02/15/2023] [Indexed: 05/20/2023] Open
Abstract
Background Subthalamic nucleus deep brain stimulation (STN-DBS) improves sleep qualities in Parkinson's disease (PD) patients; however, it remains elusive whether STN-DBS improves sleep by directly influencing the sleep circuit or alleviates other cardinal symptoms such as motor functions, other confounding factors including stimulation intensity may also involve. Studying the effect of microlesion effect (MLE) on sleep after STN-DBS electrode implantation may address this issue. Objective To examine the influence of MLE on sleep quality and related factors in PD, as well as the effects of regional and lateral specific correlations with sleep outcomes after STN-DBS electrode implantation. Study Design Case-control study; Level of evidence, 3. Data Sources and Methods In 78 PD patients who underwent bilateral STN-DBS surgery in our center, we compared the sleep qualities, motor performances, anti-Parkinsonian drug dosage, and emotional conditions at preoperative baseline and postoperative 1-month follow-up. We determined the related factors of sleep outcomes and visualized the electrodes position, simulated the MLE-engendered volume of tissue lesioned (VTL), and investigated sleep-related sweet/sour spots and laterality in STN. Results MLE improves sleep quality with Pittsburgh Sleep Quality Index (PSQI) by 13.36% and Parkinson's Disease Sleep Scale-2 (PDSS-2) by 17.95%. Motor (P = 0.014) and emotional (P = 0.001) improvements were both positively correlated with sleep improvements. However, MLE in STN associative subregions, as an independent factor, may cause sleep deterioration (r = 0.348, P = 0.002), and only the left STN showed significance (r = 0.327, P = 0.004). Sweet spot analysis also indicated part of the left STN associative subregion is the sour spot indicative of sleep deterioration. Conclusion The MLE of STN-DBS can overall improve sleep quality in PD patients, with a positive correlation between motor and emotional improvements. However, independent of all other factors, the MLE in the STN associative subregion, particularly the left side, may cause sleep deterioration.
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Affiliation(s)
- Ruoyu Ma
- Department of Neurosurgery, Beijing Tiantan
Hospital, Capital Medical University, Beijing, China
| | - Zixiao Yin
- Department of Neurosurgery, Beijing Tiantan
Hospital, Capital Medical University, Beijing, China
| | - Yingchuan Chen
- Department of Neurosurgery, Beijing Tiantan
Hospital, Capital Medical University, Beijing, China
| | - Tianshuo Yuan
- Department of Neurosurgery, Beijing Tiantan
Hospital, Capital Medical University, Beijing, China
| | - Qi An
- Department of Neurosurgery, Beijing Tiantan
Hospital, Capital Medical University, Beijing, China
| | - Yifei Gan
- Department of Neurosurgery, Beijing Tiantan
Hospital, Capital Medical University, Beijing, China
| | - Yichen Xu
- Department of Neurosurgery, Beijing Tiantan
Hospital, Capital Medical University, Beijing, China
| | - Yin Jiang
- Department of Functional Neurosurgery, Beijing
Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Tingting Du
- Department of Functional Neurosurgery, Beijing
Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Anchao Yang
- Department of Neurosurgery, Beijing Tiantan
Hospital, Capital Medical University, Beijing, China
| | - Fangang Meng
- Department of Functional Neurosurgery, Beijing
Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neurostimulation,
Beijing, China
| | - Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan
Hospital, Capital Medical University, No. 119 South 4th Ring West Road,
Fengtai District, Beijing 100070, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan
Hospital, Capital Medical University, No. 119 South 4th Ring West Road,
Fengtai District, Beijing 100070, China
- Department of Functional Neurosurgery, Beijing
Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neurostimulation,
Beijing, China
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Romanato M, Piatkowska W, Spolaor F, To DK, Volpe D, Sawacha Z. Different perspectives in understanding muscle functions in Parkinson’s disease through surface electromyography: exploring multiple activation patterns. J Electromyogr Kinesiol 2022; 64:102658. [DOI: 10.1016/j.jelekin.2022.102658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 03/29/2022] [Accepted: 04/08/2022] [Indexed: 11/25/2022] Open
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Ye F, Yang B, Nam C, Xie Y, Chen F, Hu X. A Data-Driven Investigation on Surface Electromyography Based Clinical Assessment in Chronic Stroke. Front Neurorobot 2021; 15:648855. [PMID: 34335219 PMCID: PMC8320436 DOI: 10.3389/fnbot.2021.648855] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2021] [Accepted: 06/14/2021] [Indexed: 12/23/2022] Open
Abstract
Background: Surface electromyography (sEMG) based robot-assisted rehabilitation systems have been adopted for chronic stroke survivors to regain upper limb motor function. However, the evaluation of rehabilitation effects during robot-assisted intervention relies on traditional manual assessments. This study aimed to develop a novel sEMG data-driven model for automated assessment. Method: A data-driven model based on a three-layer backpropagation neural network (BPNN) was constructed to map sEMG data to two widely used clinical scales, i.e., the Fugl-Meyer Assessment (FMA) and the Modified Ashworth Scale (MAS). Twenty-nine stroke participants were recruited in a 20-session sEMG-driven robot-assisted upper limb rehabilitation, which consisted of hand reaching and withdrawing tasks. The sEMG signals from four muscles in the paretic upper limbs, i.e., biceps brachii (BIC), triceps brachii (TRI), flexor digitorum (FD), and extensor digitorum (ED), were recorded before and after the intervention. Meanwhile, the corresponding clinical scales of FMA and MAS were measured manually by a blinded assessor. The sEMG features including Mean Absolute Value (MAV), Zero Crossing (ZC), Slope Sign Change (SSC), Root Mean Square (RMS), and Wavelength (WL) were adopted as the inputs to the data-driven model. The mapped clinical scores from the data-driven model were compared with the manual scores by Pearson correlation. Results: The BPNN, with 15 nodes in the hidden layer and sEMG features, i.e., MAV, ZC, SSC, and RMS, as the inputs to the model, was established to achieve the best mapping performance with significant correlations (r > 0.9, P < 0.001), according to the FMA. Significant correlations were also obtained between the mapped and manual FMA subscores, i.e., FMA-wrist/hand and FMA-shoulder/elbow, before and after the intervention (r > 0.9, P < 0.001). Significant correlations (P < 0.001) between the mapped and manual scores of MASs were achieved, with the correlation coefficients r = 0.91 at the fingers, 0.88 at the wrist, and 0.91 at the elbow after the intervention. Conclusion: An sEMG data-driven BPNN model was successfully developed. It could evaluate upper limb motor functions in chronic stroke and have potential application in automated assessment in post-stroke rehabilitation, once validated with large sample sizes. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT02117089.
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Affiliation(s)
- Fuqiang Ye
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
- Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Bibo Yang
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Chingyi Nam
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Yunong Xie
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Fei Chen
- Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Xiaoling Hu
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
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