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Cox E, Wade R, Hodgson R, Fulbright H, Phung TH, Meader N, Walker S, Rothery C, Simmonds M. Devices for remote continuous monitoring of people with Parkinson's disease: a systematic review and cost-effectiveness analysis. Health Technol Assess 2024; 28:1-187. [PMID: 39021200 DOI: 10.3310/ydsl3294] [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: 07/20/2024] Open
Abstract
Background Parkinson's disease is a brain condition causing a progressive loss of co ordination and movement problems. Around 145,500 people have Parkinson's disease in the United Kingdom. Levodopa is the most prescribed treatment for managing motor symptoms in the early stages. Patients should be monitored by a specialist every 6-12 months for disease progression and treatment of adverse effects. Wearable devices may provide a novel approach to management by directly monitoring patients for bradykinesia, dyskinesia, tremor and other symptoms. They are intended to be used alongside clinical judgement. Objectives To determine the clinical and cost-effectiveness of five devices for monitoring Parkinson's disease: Personal KinetiGraph, Kinesia 360, KinesiaU, PDMonitor and STAT-ON. Methods We performed systematic reviews of all evidence on the five devices, outcomes included: diagnostic accuracy, impact on decision-making, clinical outcomes, patient and clinician opinions and economic outcomes. We searched MEDLINE and 12 other databases/trial registries to February 2022. Risk of bias was assessed. Narrative synthesis was used to summarise all identified evidence, as the evidence was insufficient for meta-analysis. One included trial provided individual-level data, which was re-analysed. A de novo decision-analytic model was developed to estimate the cost-effectiveness of Personal KinetiGraph and Kinesia 360 compared to standard of care in the UK NHS over a 5-year time horizon. The base-case analysis considered two alternative monitoring strategies: one-time use and routine use of the device. Results Fifty-seven studies of Personal KinetiGraph, 15 of STAT-ON, 3 of Kinesia 360, 1 of KinesiaU and 1 of PDMonitor were included. There was some evidence to suggest that Personal KinetiGraph can accurately measure bradykinesia and dyskinesia, leading to treatment modification in some patients, and a possible improvement in clinical outcomes when measured using the Unified Parkinson's Disease Rating Scale. The evidence for STAT-ON suggested it may be of value for diagnosing symptoms, but there is currently no evidence on its clinical impact. The evidence for Kinesia 360, KinesiaU and PDMonitor is insufficient to draw any conclusions on their value in clinical practice. The base-case results for Personal KinetiGraph compared to standard of care for one-time and routine use resulted in incremental cost-effectiveness ratios of £67,856 and £57,877 per quality-adjusted life-year gained, respectively, with a beneficial impact of the Personal KinetiGraph on Unified Parkinson's Disease Rating Scale domains III and IV. The incremental cost-effectiveness ratio results for Kinesia 360 compared to standard of care for one-time and routine use were £38,828 and £67,203 per quality-adjusted life-year gained, respectively. Limitations The evidence was limited in extent and often low quality. For all devices, except Personal KinetiGraph, there was little to no evidence on the clinical impact of the technology. Conclusions Personal KinetiGraph could reasonably be used in practice to monitor patient symptoms and modify treatment where required. There is too little evidence on STAT-ON, Kinesia 360, KinesiaU or PDMonitor to be confident that they are clinically useful. The cost-effectiveness of remote monitoring appears to be largely unfavourable with incremental cost-effectiveness ratios in excess of £30,000 per quality-adjusted life-year across a range of alternative assumptions. The main driver of cost-effectiveness was the durability of improvements in patient symptoms. Study registration This study is registered as PROSPERO CRD42022308597. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR135437) and is published in full in Health Technology Assessment; Vol. 28, No. 30. See the NIHR Funding and Awards website for further award information.
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Affiliation(s)
- Edward Cox
- CHE Technology Assessment Group, University of York, York, UK
| | - Ros Wade
- CRD Technology Assessment Group, University of York, York, UK
| | - Robert Hodgson
- CRD Technology Assessment Group, University of York, York, UK
| | - Helen Fulbright
- CRD Technology Assessment Group, University of York, York, UK
| | - Thai Han Phung
- CHE Technology Assessment Group, University of York, York, UK
| | - Nicholas Meader
- CRD Technology Assessment Group, University of York, York, UK
| | - Simon Walker
- CHE Technology Assessment Group, University of York, York, UK
| | - Claire Rothery
- CHE Technology Assessment Group, University of York, York, UK
| | - Mark Simmonds
- CRD Technology Assessment Group, University of York, York, UK
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Zampogna A, Borzì L, Rinaldi D, Artusi CA, Imbalzano G, Patera M, Lopiano L, Pontieri F, Olmo G, Suppa A. Unveiling the Unpredictable in Parkinson's Disease: Sensor-Based Monitoring of Dyskinesias and Freezing of Gait in Daily Life. Bioengineering (Basel) 2024; 11:440. [PMID: 38790307 PMCID: PMC11117481 DOI: 10.3390/bioengineering11050440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 04/23/2024] [Accepted: 04/28/2024] [Indexed: 05/26/2024] Open
Abstract
BACKGROUND Dyskinesias and freezing of gait are episodic disorders in Parkinson's disease, characterized by a fluctuating and unpredictable nature. This cross-sectional study aims to objectively monitor Parkinsonian patients experiencing dyskinesias and/or freezing of gait during activities of daily living and assess possible changes in spatiotemporal gait parameters. METHODS Seventy-one patients with Parkinson's disease (40 with dyskinesias and 33 with freezing of gait) were continuously monitored at home for a minimum of 5 days using a single wearable sensor. Dedicated machine-learning algorithms were used to categorize patients based on the occurrence of dyskinesias and freezing of gait. Additionally, specific spatiotemporal gait parameters were compared among patients with and without dyskinesias and/or freezing of gait. RESULTS The wearable sensor algorithms accurately classified patients with and without dyskinesias as well as those with and without freezing of gait based on the recorded dyskinesias and freezing of gait episodes. Standard spatiotemporal gait parameters did not differ significantly between patients with and without dyskinesias or freezing of gait. Both the time spent with dyskinesias and the number of freezing of gait episodes positively correlated with the disease severity and medication dosage. CONCLUSIONS A single inertial wearable sensor shows promise in monitoring complex, episodic movement patterns, such as dyskinesias and freezing of gait, during daily activities. This approach may help implement targeted therapeutic and preventive strategies for Parkinson's disease.
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Affiliation(s)
- Alessandro Zampogna
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy; (A.Z.); (M.P.)
- IRCCS Neuromed Institute, 86077 Pozzilli, IS, Italy
| | - Luigi Borzì
- Data Analytics and Technologies for Health Lab (ANTHEA), Department of Control and Computer Engineering, Politecnico di Torino, 10129 Turin, Italy; (L.B.); (G.O.)
| | - Domiziana Rinaldi
- Department of Neuroscience, Mental Health and Sense Organs (NESMOS), Sapienza University of Rome, 00189 Rome, Italy; (D.R.); (F.P.)
| | - Carlo Alberto Artusi
- Department of Neuroscience “Rita Levi Montalcini”, University of Turin, 10126 Torino, Italy; (C.A.A.); (G.I.); (L.L.)
- Neurology 2 Unit, A.O.U, Città della Salute e della Scienza di Torino, 10126 Torino, Italy
| | - Gabriele Imbalzano
- Department of Neuroscience “Rita Levi Montalcini”, University of Turin, 10126 Torino, Italy; (C.A.A.); (G.I.); (L.L.)
| | - Martina Patera
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy; (A.Z.); (M.P.)
| | - Leonardo Lopiano
- Department of Neuroscience “Rita Levi Montalcini”, University of Turin, 10126 Torino, Italy; (C.A.A.); (G.I.); (L.L.)
- Neurology 2 Unit, A.O.U, Città della Salute e della Scienza di Torino, 10126 Torino, Italy
| | - Francesco Pontieri
- Department of Neuroscience, Mental Health and Sense Organs (NESMOS), Sapienza University of Rome, 00189 Rome, Italy; (D.R.); (F.P.)
| | - Gabriella Olmo
- Data Analytics and Technologies for Health Lab (ANTHEA), Department of Control and Computer Engineering, Politecnico di Torino, 10129 Turin, Italy; (L.B.); (G.O.)
| | - Antonio Suppa
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy; (A.Z.); (M.P.)
- IRCCS Neuromed Institute, 86077 Pozzilli, IS, Italy
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Guerra A, D'Onofrio V, Ferreri F, Bologna M, Antonini A. Objective measurement versus clinician-based assessment for Parkinson's disease. Expert Rev Neurother 2023; 23:689-702. [PMID: 37366316 DOI: 10.1080/14737175.2023.2229954] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 06/18/2023] [Accepted: 06/22/2023] [Indexed: 06/28/2023]
Abstract
INTRODUCTION Although clinician-based assessment through standardized clinical rating scales is currently the gold standard for quantifying motor impairment in Parkinson's disease (PD), it is not without limitations, including intra- and inter-rater variability and a degree of approximation. There is increasing evidence supporting the use of objective motion analyses to complement clinician-based assessment. Objective measurement tools hold significant potential for improving the accuracy of clinical and research-based evaluations of patients. AREAS COVERED The authors provide several examples from the literature demonstrating how different motion measurement tools, including optoelectronics, contactless and wearable systems allow for both the objective quantification and monitoring of key motor symptoms (such as bradykinesia, rigidity, tremor, and gait disturbances), and the identification of motor fluctuations in PD patients. Furthermore, they discuss how, from a clinician's perspective, objective measurements can help in various stages of PD management. EXPERT OPINION In our opinion, sufficient evidence supports the assertion that objective monitoring systems enable accurate evaluation of motor symptoms and complications in PD. A range of devices can be utilized not only to support diagnosis but also to monitor motor symptom during the disease progression and can become relevant in the therapeutic decision-making process.
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Affiliation(s)
- Andrea Guerra
- Parkinson and Movement Disorder Unit, Study Center on Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua, Italy
| | | | - Florinda Ferreri
- Unit of Neurology, Unit of Clinical Neurophysiology, Study Center of Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua, Italy
- Department of Clinical Neurophysiology, Kuopio University Hospital, University of Eastern Finland, Kuopio, Finland
| | - Matteo Bologna
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
- IRCCS Neuromed, Pozzilli, Italy
| | - Angelo Antonini
- Parkinson and Movement Disorder Unit, Study Center on Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua, Italy
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Qamar MA, Rota S, Batzu L, Subramanian I, Falup-Pecurariu C, Titova N, Metta V, Murasan L, Odin P, Padmakumar C, Kukkle PL, Borgohain R, Kandadai RM, Goyal V, Chaudhuri KR. Chaudhuri's Dashboard of Vitals in Parkinson's syndrome: an unmet need underpinned by real life clinical tests. Front Neurol 2023; 14:1174698. [PMID: 37305739 PMCID: PMC10248458 DOI: 10.3389/fneur.2023.1174698] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 05/02/2023] [Indexed: 06/13/2023] Open
Abstract
We have recently published the notion of the "vitals" of Parkinson's, a conglomeration of signs and symptoms, largely nonmotor, that must not be missed and yet often not considered in neurological consultations, with considerable societal and personal detrimental consequences. This "dashboard," termed the Chaudhuri's vitals of Parkinson's, are summarized as 5 key vital symptoms or signs and comprise of (a) motor, (b) nonmotor, (c) visual, gut, and oral health, (d) bone health and falls, and finally (e) comorbidities, comedication, and dopamine agonist side effects, such as impulse control disorders. Additionally, not addressing the vitals also may reflect inadequate management strategies, leading to worsening quality of life and diminished wellness, a new concept for people with Parkinson's. In this paper, we discuss possible, simple to use, and clinically relevant tests that can be used to monitor the status of these vitals, so that these can be incorporated into clinical practice. We also use the term Parkinson's syndrome to describe Parkinson's disease, as the term "disease" is now abandoned in many countries, such as the U.K., reflecting the heterogeneity of Parkinson's, which is now considered by many as a syndrome.
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Affiliation(s)
- Mubasher A. Qamar
- Institute of Psychiatry, Psychology and Neuroscience, Department of Basic and Clinical Neuroscience, Division of Neuroscience, King’s College London, London, United Kingdom
- King’s College Hospital NHS Foundation Trust, London, United Kingdom
| | - Silvia Rota
- Institute of Psychiatry, Psychology and Neuroscience, Department of Basic and Clinical Neuroscience, Division of Neuroscience, King’s College London, London, United Kingdom
- King’s College Hospital NHS Foundation Trust, London, United Kingdom
| | - Lucia Batzu
- Institute of Psychiatry, Psychology and Neuroscience, Department of Basic and Clinical Neuroscience, Division of Neuroscience, King’s College London, London, United Kingdom
- King’s College Hospital NHS Foundation Trust, London, United Kingdom
| | - Indu Subramanian
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Parkinson’s Disease Research, Education and Clinical Centers, Greater Los Angeles Veterans Affairs Medical Center, Los Angeles, CA, United States
| | - Cristian Falup-Pecurariu
- Faculty of Medicine, Transilvania University of Braşov, Brașov, Romania
- Department of Neurology, County Clinic Hospital, Brașov, Romania
| | - Nataliya Titova
- Department of Neurology, Neurosurgery and Medical Genetics, Federal State Autonomous Educational Institution of Higher Education “N.I. Pirogov Russian National Research Medical University” of the Ministry of Health of the Russian Federation, Moscow, Russia
- Department of Neurodegenerative Diseases, Federal State Budgetary Institution “Federal Center of Brain Research and Neurotechnologies” of the Federal Medical Biological Agency, Moscow, Russia
| | - Vinod Metta
- Institute of Psychiatry, Psychology and Neuroscience, Department of Basic and Clinical Neuroscience, Division of Neuroscience, King’s College London, London, United Kingdom
- King’s College Hospital NHS Foundation Trust, London, United Kingdom
| | - Lulia Murasan
- Faculty of Medicine, Transilvania University of Braşov, Brașov, Romania
- Department of Neurology, County Clinic Hospital, Brașov, Romania
| | - Per Odin
- Department of Neurology, University Hospital, Lund, Sweden
| | | | - Prashanth L. Kukkle
- Center for Parkinson’s Disease and Movement Disorders, Manipal Hospital, Karnataka, India, Bangalore
- Parkinson’s Disease and Movement Disorders Clinic, Bangalore, Karnataka, India
| | - Rupam Borgohain
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Rukmini Mridula Kandadai
- Department of Neurology, Nizam’s Institute of Medical Sciences, Autonomous University, Hyderabad, India
| | - Vinay Goyal
- Neurology Department, Medanta, Gurugram, India
| | - Kallo Ray Chaudhuri
- Institute of Psychiatry, Psychology and Neuroscience, Department of Basic and Clinical Neuroscience, Division of Neuroscience, King’s College London, London, United Kingdom
- King’s College Hospital NHS Foundation Trust, London, United Kingdom
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Gonzales MM, Wang D, Pollet E, Velarde Á, Horn S, Coss P, Vaou O, Wang J, Li C, Seshadri S, Miao H, González DA. Pilot Study Results Assessing the Accuracy of a Ballistic Sleep Monitor Relative to Polysomnography in Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2023; 13:1073-1076. [PMID: 37599538 PMCID: PMC10578264 DOI: 10.3233/jpd-230126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 08/02/2023] [Indexed: 08/22/2023]
Affiliation(s)
- Mitzi M. Gonzales
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Duo Wang
- Department of Statistics, Florida State University, Tallahassee, FL, USA
| | - Erin Pollet
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Academy Diagnostics Sleep and EEG Center, 8215 Fredericksburg Road, San Antonio, TX, USA
| | - Ángel Velarde
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Sarah Horn
- Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Pablo Coss
- Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Okeanis Vaou
- Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Jing Wang
- College of Nursing, Florida State University, Tallahassee, FL, USA
| | - Chengdong Li
- College of Nursing, Florida State University, Tallahassee, FL, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Hongyu Miao
- Department of Statistics, Florida State University, Tallahassee, FL, USA
- College of Nursing, Florida State University, Tallahassee, FL, USA
| | - David Andrés González
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
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Hu H, Xiao D, Rhodin H, Murphy TH. Towards a Visualizable, De-identified Synthetic Biomarker of Human Movement Disorders. JOURNAL OF PARKINSON'S DISEASE 2022; 1:2085-2096. [PMID: 36057831 PMCID: PMC10473142 DOI: 10.3233/jpd-223351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 08/10/2022] [Indexed: 12/15/2022]
Abstract
Human motion analysis has been a common thread across modern and early medicine. While medicine evolves, analysis of movement disorders is mostly based on clinical presentation and trained observers making subjective assessments using clinical rating scales. Currently, the field of computer vision has seen exponential growth and successful medical applications. While this has been the case, neurology, for the most part, has not embraced digital movement analysis. There are many reasons for this including: the limited size of labeled datasets, accuracy and nontransparent nature of neural networks, and potential legal and ethical concerns. We hypothesize that a number of opportunities are made available by advancements in computer vision that will enable digitization of human form, movements, and will represent them synthetically in 3D. Representing human movements within synthetic body models will potentially pave the way towards objective standardized digital movement disorder diagnosis and building sharable open-source datasets from such processed videos. We provide a perspective of this emerging field and describe how clinicians and computer scientists can navigate this new space. Such digital movement capturing methods will be important for both machine learning-based diagnosis and computer vision-aided clinical assessment. It would also supplement face-to-face clinical visits and be used for longitudinal monitoring and remote diagnosis.
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Affiliation(s)
- Hao Hu
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, Vancouver, BC, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Dongsheng Xiao
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, Vancouver, BC, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Helge Rhodin
- Department of Computer Science, University of British Columbia, Vancouver, BC, Canada
| | - Timothy H. Murphy
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, Vancouver, BC, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
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Ergonomic Assessment of Physical Load in Slovak Industry Using Wearable Technologies. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12073607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The physical tasks of workers are demanding, particularly when performed long-term in unsuitable working position, with high frequency, heavy load, after injury, with developing damage of health or reduced performance due to advanced age. Work-related musculoskeletal disorders (WMSDs) result from overuse or develop over time. Work activities, which are frequent and repetitive, or activities with awkward postures, cause disorders that may be painful during work or at rest. There is a new technology in the market, occupational exoskeletons, which have the prerequisites for minimizing the negative consequences of workload on WMSDs. We provided pilot quantitative measurements of the ergonomic risk at one selected workplace in a Slovak automotive company with four different workers to prove our methodology using wearable wireless multi-sensor systems Captiv and Actigraph. At first, the test was performed in standard conditions without an exoskeleton. The unacceptable physical load was identified in considerable evaluated body areas—neck, hip, and shoulder. Next, the passive chair exoskeleton Chairless Chair 2.0 was used in trials as an ergonomic measure. Our intention was to determine whether an exoskeleton would be an effective tool for optimizing the workload in selected workplaces and whether the proposed unique quantitative measurement system would give reliable and quick results.
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Asci F, Vivacqua G, Zampogna A, D’Onofrio V, Mazzeo A, Suppa A. Wearable Electrochemical Sensors in Parkinson's Disease. SENSORS 2022; 22:s22030951. [PMID: 35161694 PMCID: PMC8839454 DOI: 10.3390/s22030951] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 01/19/2022] [Accepted: 01/24/2022] [Indexed: 12/15/2022]
Abstract
Parkinson’s disease (PD) is a neurodegenerative disorder associated with widespread aggregation of α-synuclein and dopaminergic neuronal loss in the substantia nigra pars compacta. As a result, striatal dopaminergic denervation leads to functional changes in the cortico-basal-ganglia-thalamo-cortical loop, which in turn cause most of the parkinsonian signs and symptoms. Despite tremendous advances in the field in the last two decades, the overall management (i.e., diagnosis and follow-up) of patients with PD remains largely based on clinical procedures. Accordingly, a relevant advance in the field would require the development of innovative biomarkers for PD. Recently, the development of miniaturized electrochemical sensors has opened new opportunities in the clinical management of PD thanks to wearable devices able to detect specific biological molecules from various body fluids. We here first summarize the main wearable electrochemical technologies currently available and their possible use as medical devices. Then, we critically discuss the possible strengths and weaknesses of wearable electrochemical devices in the management of chronic diseases including PD. Finally, we speculate about possible future applications of wearable electrochemical sensors in PD, such as the attractive opportunity for personalized closed-loop therapeutic approaches.
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Affiliation(s)
| | - Giorgio Vivacqua
- Integrated Research Center (PRAAB), Campus Biomedico University of Roma, Via Alvaro del Portillo 21, 00125 Rome, RM, Italy;
| | - Alessandro Zampogna
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, RM, Italy; (A.Z.); (V.D.); (A.M.)
| | - Valentina D’Onofrio
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, RM, Italy; (A.Z.); (V.D.); (A.M.)
| | - Adolfo Mazzeo
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, RM, Italy; (A.Z.); (V.D.); (A.M.)
| | - Antonio Suppa
- IRCCS Neuromed, 86077 Pozzilli, IS, Italy;
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, RM, Italy; (A.Z.); (V.D.); (A.M.)
- Correspondence: ; Tel.: +39-06-49914544
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Hallett M, DelRosso LM, Elble R, Ferri R, Horak FB, Lehericy S, Mancini M, Matsuhashi M, Matsumoto R, Muthuraman M, Raethjen J, Shibasaki H. Evaluation of movement and brain activity. Clin Neurophysiol 2021; 132:2608-2638. [PMID: 34488012 PMCID: PMC8478902 DOI: 10.1016/j.clinph.2021.04.023] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 04/07/2021] [Accepted: 04/25/2021] [Indexed: 11/25/2022]
Abstract
Clinical neurophysiology studies can contribute important information about the physiology of human movement and the pathophysiology and diagnosis of different movement disorders. Some techniques can be accomplished in a routine clinical neurophysiology laboratory and others require some special equipment. This review, initiating a series of articles on this topic, focuses on the methods and techniques. The methods reviewed include EMG, EEG, MEG, evoked potentials, coherence, accelerometry, posturography (balance), gait, and sleep studies. Functional MRI (fMRI) is also reviewed as a physiological method that can be used independently or together with other methods. A few applications to patients with movement disorders are discussed as examples, but the detailed applications will be the subject of other articles.
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Affiliation(s)
- Mark Hallett
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA.
| | | | - Rodger Elble
- Department of Neurology, Southern Illinois University School of Medicine, Springfield, IL, USA
| | | | - Fay B Horak
- Department of Neurology, Oregon Health & Science University, Portland, OR, USA
| | - Stephan Lehericy
- Paris Brain Institute (ICM), Centre de NeuroImagerie de Recherche (CENIR), Team "Movement, Investigations and Therapeutics" (MOV'IT), INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
| | - Martina Mancini
- Department of Neurology, Oregon Health & Science University, Portland, OR, USA
| | - Masao Matsuhashi
- Department of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate, School of Medicine, Japan
| | - Riki Matsumoto
- Division of Neurology, Kobe University Graduate School of Medicine, Japan
| | - Muthuraman Muthuraman
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Jan Raethjen
- Neurology Outpatient Clinic, Preusserstr. 1-9, 24105 Kiel, Germany
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Zampogna A, Mileti I, Martelli F, Paoloni M, Del Prete Z, Palermo E, Suppa A. Early balance impairment in Parkinson's Disease: Evidence from Robot-assisted axial rotations. Clin Neurophysiol 2021; 132:2422-2430. [PMID: 34454269 DOI: 10.1016/j.clinph.2021.06.023] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 05/27/2021] [Accepted: 06/06/2021] [Indexed: 12/20/2022]
Abstract
OBJECTIVE Early postural instability (PI) is a red flag for the diagnosis of Parkinson's disease (PD). Several patients, however, fall within the first three years of disease, particularly when turning. We investigated whether PD patients, without clinically overt PI, manifest abnormal reactive postural responses to ecological perturbations resembling turning. METHODS Fifteen healthy subjects and 20 patients without clinically overt PI, under and not under L-Dopa, underwent dynamic posturography during axial rotations around the longitudinal axis, provided by a robotic mechatronic platform. We measured reactive postural responses, including body displacement and reciprocal movements of the head, trunk, and pelvis, by using a network of three wearable inertial sensors. RESULTS Patients showed higher body displacement of the head, trunk and pelvis, and lower joint movements at the lumbo-sacral junction than controls. Conversely, movements at the cranio-cervical junction were normal in PD. L-Dopa left reactive postural responses unchanged. CONCLUSIONS Patients with PD without clinically overt PI manifest abnormal reactive postural responses to axial rotations, unresponsive to L-Dopa. The biomechanical model resulting from our experimental approach supports novel pathophysiological hypotheses of abnormal axial rotations in PD. SIGNIFICANCE PD patients without clinically overt PI present subclinical balance impairment during axial rotations, unresponsive to L-Dopa.
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Affiliation(s)
- Alessandro Zampogna
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Ilaria Mileti
- Mechanical Measurements and Microelectronics (M3Lab) Lab, Engineering Department, University Niccolò Cusano, 00166 Rome, Italy
| | - Francesca Martelli
- Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy
| | - Marco Paoloni
- Department of Physical Medicine and Rehabilitation, Sapienza University of Rome, 00161 Rome, Italy
| | - Zaccaria Del Prete
- Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy
| | - Eduardo Palermo
- Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy
| | - Antonio Suppa
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy; IRCCS Neuromed, 86077 Pozzilli, IS, Italy.
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Saoutieff E, Polichetti T, Jouanet L, Faucon A, Vidal A, Pereira A, Boisseau S, Ernst T, Miglietta ML, Alfano B, Massera E, De Vito S, Bui DHN, Benech P, Vuong TP, Moldovan C, Danlee Y, Walewyns T, Petre S, Flandre D, Ancans A, Greitans M, Ionescu AM. A Wearable Low-Power Sensing Platform for Environmental and Health Monitoring: The Convergence Project. SENSORS (BASEL, SWITZERLAND) 2021; 21:1802. [PMID: 33807664 PMCID: PMC7961452 DOI: 10.3390/s21051802] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 02/24/2021] [Accepted: 02/28/2021] [Indexed: 12/16/2022]
Abstract
The low-power sensing platform proposed by the Convergence project is foreseen as a wireless, low-power and multifunctional wearable system empowered by energy-efficient technologies. This will allow meeting the strict demands of life-style and healthcare applications in terms of autonomy for quasi-continuous collection of data for early-detection strategies. The system is compatible with different kinds of sensors, able to monitor not only health indicators of individual person (physical activity, core body temperature and biomarkers) but also the environment with chemical composition of the ambient air (NOx, COx, NHx particles) returning meaningful information on his/her exposure to dangerous (safety) or pollutant agents. In this article, we introduce the specifications and the design of the low-power sensing platform and the different sensors developed in the project, with a particular focus on pollutant sensing capabilities and specifically on NO2 sensor based on graphene and CO sensor based on polyaniline ink.
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Affiliation(s)
- Elise Saoutieff
- Univ. Grenoble Alpes, CEA, LETI, F-38000 Grenoble, France; (L.J.); (A.F.); (A.V.); (S.B.); (T.E.)
| | - Tiziana Polichetti
- ENEA CR-Portici, TERIN-FSD Department, P.le E. Fermi 1, 80055 Portici, Italy; (T.P.); (M.L.M.); (B.A.); (E.M.); (S.D.V.)
| | - Laurent Jouanet
- Univ. Grenoble Alpes, CEA, LETI, F-38000 Grenoble, France; (L.J.); (A.F.); (A.V.); (S.B.); (T.E.)
| | - Adrien Faucon
- Univ. Grenoble Alpes, CEA, LETI, F-38000 Grenoble, France; (L.J.); (A.F.); (A.V.); (S.B.); (T.E.)
| | - Audrey Vidal
- Univ. Grenoble Alpes, CEA, LETI, F-38000 Grenoble, France; (L.J.); (A.F.); (A.V.); (S.B.); (T.E.)
| | | | - Sébastien Boisseau
- Univ. Grenoble Alpes, CEA, LETI, F-38000 Grenoble, France; (L.J.); (A.F.); (A.V.); (S.B.); (T.E.)
| | - Thomas Ernst
- Univ. Grenoble Alpes, CEA, LETI, F-38000 Grenoble, France; (L.J.); (A.F.); (A.V.); (S.B.); (T.E.)
| | - Maria Lucia Miglietta
- ENEA CR-Portici, TERIN-FSD Department, P.le E. Fermi 1, 80055 Portici, Italy; (T.P.); (M.L.M.); (B.A.); (E.M.); (S.D.V.)
| | - Brigida Alfano
- ENEA CR-Portici, TERIN-FSD Department, P.le E. Fermi 1, 80055 Portici, Italy; (T.P.); (M.L.M.); (B.A.); (E.M.); (S.D.V.)
| | - Ettore Massera
- ENEA CR-Portici, TERIN-FSD Department, P.le E. Fermi 1, 80055 Portici, Italy; (T.P.); (M.L.M.); (B.A.); (E.M.); (S.D.V.)
| | - Saverio De Vito
- ENEA CR-Portici, TERIN-FSD Department, P.le E. Fermi 1, 80055 Portici, Italy; (T.P.); (M.L.M.); (B.A.); (E.M.); (S.D.V.)
| | - Do Hanh Ngan Bui
- GINP, IMEP-LAHC, INP Grenoble—Minatec, 3 Parvis Louis Néel, CS 50257, F-38016 Grenoble, France; (D.H.N.B.); (P.B.); (T.-P.V.)
| | - Philippe Benech
- GINP, IMEP-LAHC, INP Grenoble—Minatec, 3 Parvis Louis Néel, CS 50257, F-38016 Grenoble, France; (D.H.N.B.); (P.B.); (T.-P.V.)
| | - Tan-Phu Vuong
- GINP, IMEP-LAHC, INP Grenoble—Minatec, 3 Parvis Louis Néel, CS 50257, F-38016 Grenoble, France; (D.H.N.B.); (P.B.); (T.-P.V.)
| | - Carmen Moldovan
- National Institute for R&D in Microtechnologies, 077190 Voluntari, Romania;
| | - Yann Danlee
- ICTEAM, Université Catholique de Louvain (UCLouvain), 1348 Louvain-la-Neuve, Belgium; (Y.D.); (T.W.); (S.P.); (D.F.)
| | - Thomas Walewyns
- ICTEAM, Université Catholique de Louvain (UCLouvain), 1348 Louvain-la-Neuve, Belgium; (Y.D.); (T.W.); (S.P.); (D.F.)
| | - Sylvain Petre
- ICTEAM, Université Catholique de Louvain (UCLouvain), 1348 Louvain-la-Neuve, Belgium; (Y.D.); (T.W.); (S.P.); (D.F.)
| | - Denis Flandre
- ICTEAM, Université Catholique de Louvain (UCLouvain), 1348 Louvain-la-Neuve, Belgium; (Y.D.); (T.W.); (S.P.); (D.F.)
| | - Armands Ancans
- Institute of Electronics and Computer Science, 1006 Riga, Latvia; (A.A.); (M.G.)
| | - Modris Greitans
- Institute of Electronics and Computer Science, 1006 Riga, Latvia; (A.A.); (M.G.)
| | - Adrian M. Ionescu
- NanoLab, Ecole Polytechnique Federale de Lausanne (EPFL), 1015 Lausanne, Switzerland;
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Thun-Hohenstein C, Klucken J. Wearables als unterstützendes Tool für den Paradigmenwechsel in der Versorgung von Parkinson Patienten. KLIN NEUROPHYSIOL 2021. [DOI: 10.1055/a-1353-9413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
ZusammenfassungTragbare Sensoren – „Wearables“ – eignen sich, Funktionsstörungen bei Parkinson Patienten zu erheben und werden zur Prävention, Prädiktion, Diagnostik und Therapieunterstützung genutzt. In der Forschung erhöhen sie die Reliabilität der erhobenen Daten und stellen bessere Studien-Endpunkte dar, als die herkömmlichen, subjektiven und wenig quantitativen Rating- und Selbstbeurteilungsskalen. Untersucht werden motorische Symptome wie Tremor, Bradykinese und Gangstörungen und auch nicht motorische Symptome. In der Home-Monitoringanwendung kann der Ist-Zustand des Patienten im realen Leben untersucht werden, die Therapie überwacht, die Adhärenz verbessert und die Compliance überprüft werden. Zusätzlich können Wearables interventionell zur Verbesserung von Symptomen eingesetzt werden wie z. B. Cueing, Gamification oder Coaching. Der Transfer von Laborbedingungen in den häuslichen Alltag ist eine medizinisch-technische Herausforderung. Optimierte Versorgungsmodelle müssen entwickelt werden und der tatsächliche Nutzen für den individuellen Patienten in weiteren Studien belegt werden.
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Affiliation(s)
| | - Jochen Klucken
- Molekulare Neurologie, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg
- Fraunhofer IIS, Erlangen
- Medical Valley Digital Health Application Center GmbH, Bamberg
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