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Tucak C, Chih H, Mastaglia F, Rodrigues J. The 'PD Warrior' exercise programme improves motor outcomes and quality of life in patients with early Parkinson disease: results of a pilot study. Intern Med J 2024; 54:823-832. [PMID: 38100122 DOI: 10.1111/imj.16301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 11/19/2023] [Indexed: 05/18/2024]
Abstract
BACKGROUND 'PD Warrior' (PDW) is a popular exercise programme for Parkinson disease; however, there are no published studies on the outcomes of the programme. AIMS To investigate short-term functional and quality of life (QoL) outcomes after the PDW 10-week programme in a pilot study of individuals with early Parkinson Disease (PD). METHODS Twenty individuals with PD (Hoehn & Yahr 1-3) attending a hospital outpatient clinic were recruited into the PDW 10-week programme, comprising a weekly 1-h supervised class complemented by an individualised daily home exercise programme. Participants had the following assessments at baseline and after completion of the programme: Movement Disorder Society Unified Parkinson Disease Rating Scale (MDS-UPDRS) Part III, timed up-and-go (TUG), 10-m walk test (10mWT), 6-min walking test (6MWT), balance tests, fine motor skills, 7-day Parkinson KinetiGraph (PKG) and PDQ-39 QoL scale. RESULTS Seventeen individuals completed the programme. Significant improvements were observed in MDS-UPDRS motor score (P = 0.019, d = 0.68, MCID 7); 6MWT distance (P < 0.001, d = 1.16); walking time during motor or cognitive dual tasking (P = 0.006, d = 0.77; P = 0.005, d = 0.79, respectively); and the PDQ-39 emotional well-being subdomain (P = 0.009; MCID 4.2); as well as improvements trending to significance in bradykinesia (P = 0.025, d = 0.73), 10mWT walking time (P = 0.023, d = 0.61) and borderline improvement in balance (P = 0.056, d = 0.50). CONCLUSIONS The outcomes of this study support the efficacy of the PDW programme in individuals with early PD and provide justification for future trials and investigation of its effects.
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Affiliation(s)
- Claire Tucak
- Physiotherapy Department, Hollywood Private Hospital, Nedlands, Western Australia, Australia
- Perron Institute for Neurological and Translational Science, Nedlands, Western Australia, Australia
- Physiotherapy Department, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- University of Western Australia, Perth, Western Australia, Australia
| | - HuiJun Chih
- Curtin School of Population Health, Clinical Trials Enabling Platform, Curtin University, Perth, Western Australia, Australia
| | - Frank Mastaglia
- Perron Institute for Neurological and Translational Science, Nedlands, Western Australia, Australia
- University of Western Australia, Perth, Western Australia, Australia
- Queen Elizabeth II Medical Centre, Perth, Western Australia, Australia
| | - Julian Rodrigues
- Perth Neurology Clinic, Hollywood Private Hospital, Nedlands, Western Australia, Australia
- Fiona Stanley Hospital, Murdoch, Western Australia, Australia
- Neurosciences Queensland, Spring Hill, Queensland, Australia
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Kehagia AA, Chowienczyk S, Helena van Velthoven M, King E, North T, Shenton D, Abraham J, Langley J, Partridge R, Ankeny U, Gorst T, Edwards E, Whipps S, Batup M, Rideout J, Swabey M, Inches J, Bentley S, Gilbert G, Carroll C. Real-World Evaluation of the Feasibility, Acceptability and Safety of a Remote, Self-Management Parkinson's Disease Care Pathway: A Healthcare Improvement Initiative. JOURNAL OF PARKINSON'S DISEASE 2024; 14:197-208. [PMID: 38250784 PMCID: PMC10836560 DOI: 10.3233/jpd-230205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Indexed: 01/23/2024]
Abstract
BACKGROUND There is significant unmet need for effective and efficiently delivered care for people with Parkinson's disease (PwP). We undertook a service improvement initiative to co-develop and implement a new care pathway, Home Based Care (HBC), based on supported self-management, remote monitoring and the ability to trigger a healthcare contact when needed. OBJECTIVE To evaluate feasibility, acceptability and safety of Home Based Care. METHODS We evaluated data from the first 100 patients on HBC for 6 months. Patient monitoring, performed at baseline and 6-monthly, comprised motor (MDS-UPDRS II and accelerometer), non-motor (NMSQ, PDSS-2, HADS) and quality of life (PDQ) measures. Care quality was audited against Parkinson's UK national audit standards. Process measures captured feasibility. Acceptability was assessed using a mixed-methods approach comprising questionnaires and semi-structured interviews. RESULTS Between October 2019 and January 2021, 108 PwP were enrolled onto HBC, with data from 100 being available at 6 months. Over 90% of all questionnaires were returned, 97% were complete or had < 3 missing items. Reporting and communications occurred within agreed timeframes. Compared with baseline, after 6m on HBC, PD symptoms were stable; more PwP felt listened to (90% vs. 79%) and able to seek help (79% vs. 68%). HBC met 93% of national audit criteria. Key themes from the interviews included autonomy and empowerment. CONCLUSIONS We have demonstrated acceptability, feasibility and safety of our novel remotely delivered Parkinson's care pathway. Ensuring scalability will widen its reach and realize its benefits for underserved communities, enabling formal comparisons with standard care and cost-effectiveness evaluation.
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Affiliation(s)
- Angie A. Kehagia
- School of Biomedical Engineering and Imaging Sciences, King’s Technology Evaluation Centre, King’s College London, UK
- University of Plymouth, Plymouth, UK
| | | | | | - Emma King
- University Hospitals Plymouth NHS Trust, Plymouth, UK
| | | | | | | | | | | | | | - Terry Gorst
- South West Academic Health Science Network, Exeter, UK
| | | | | | | | | | - Mat Swabey
- University Hospitals Plymouth NHS Trust, Plymouth, UK
| | - Jemma Inches
- University Hospitals Plymouth NHS Trust, Plymouth, UK
| | - Sue Bentley
- University Hospitals Plymouth NHS Trust, Plymouth, UK
| | | | - Camille Carroll
- University of Plymouth, Plymouth, UK
- University Hospitals Plymouth NHS Trust, Plymouth, UK
- Newcastle University Translational and Clinical Research Institute, Newcastle, UK
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Moreau C, Rouaud T, Grabli D, Benatru I, Remy P, Marques AR, Drapier S, Mariani LL, Roze E, Devos D, Dupont G, Bereau M, Fabbri M. Overview on wearable sensors for the management of Parkinson's disease. NPJ Parkinsons Dis 2023; 9:153. [PMID: 37919332 PMCID: PMC10622581 DOI: 10.1038/s41531-023-00585-y] [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: 05/25/2023] [Accepted: 10/02/2023] [Indexed: 11/04/2023] Open
Abstract
Parkinson's disease (PD) is affecting about 1.2 million patients in Europe with a prevalence that is expected to have an exponential increment, in the next decades. This epidemiological evolution will be challenged by the low number of neurologists able to deliver expert care for PD. As PD is better recognized, there is an increasing demand from patients for rigorous control of their symptoms and for therapeutic education. In addition, the highly variable nature of symtoms between patients and the fluctuations within the same patient requires innovative tools to help doctors and patients monitor the disease in their usual living environment and adapt treatment in a more relevant way. Nowadays, there are various body-worn sensors (BWS) proposed to monitor parkinsonian clinical features, such as motor fluctuations, dyskinesia, tremor, bradykinesia, freezing of gait (FoG) or gait disturbances. BWS have been used as add-on tool for patients' management or research purpose. Here, we propose a practical anthology, summarizing the characteristics of the most used BWS for PD patients in Europe, focusing on their role as tools to improve treatment management. Consideration regarding the use of technology to monitor non-motor features is also included. BWS obviously offer new opportunities for improving management strategy in PD but their precise scope of use in daily routine care should be clarified.
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Affiliation(s)
- Caroline Moreau
- Department of Neurology, Parkinson's disease expert Center, Lille University, INSERM UMRS_1172, University Hospital Center, Lille, France
- The French Ns-Park Network, Paris, France
| | - Tiphaine Rouaud
- The French Ns-Park Network, Paris, France
- CHU Nantes, Centre Expert Parkinson, Department of Neurology, Nantes, F-44093, France
| | - David Grabli
- The French Ns-Park Network, Paris, France
- Assistance Publique Hôpitaux de Paris, Department of Neurology, CIC Neurosciences, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Sorbonne University, Paris Brain Institute - ICM, Inserm, CNRS, Paris, France
| | - Isabelle Benatru
- The French Ns-Park Network, Paris, France
- Department of Neurology, University Hospital of Poitiers, Poitiers, France
- INSERM, CHU de Poitiers, University of Poitiers, Centre d'Investigation Clinique CIC1402, Poitiers, France
| | - Philippe Remy
- The French Ns-Park Network, Paris, France
- Centre Expert Parkinson, NS-Park/FCRIN Network, CHU Henri Mondor, AP-HP, Equipe NPI, IMRB, INSERM et Faculté de Santé UPE-C, Créteil, FranceService de neurologie, hôpital Henri-Mondor, AP-HP, Créteil, France
| | - Ana-Raquel Marques
- The French Ns-Park Network, Paris, France
- Université Clermont Auvergne, CNRS, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand University Hospital, Neurology department, Clermont-Ferrand, France
| | - Sophie Drapier
- The French Ns-Park Network, Paris, France
- Pontchaillou University Hospital, Department of Neurology, CIC INSERM 1414, Rennes, France
| | - Louise-Laure Mariani
- The French Ns-Park Network, Paris, France
- Assistance Publique Hôpitaux de Paris, Department of Neurology, CIC Neurosciences, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Sorbonne University, Paris Brain Institute - ICM, Inserm, CNRS, Paris, France
| | - Emmanuel Roze
- The French Ns-Park Network, Paris, France
- Assistance Publique Hôpitaux de Paris, Department of Neurology, CIC Neurosciences, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Sorbonne University, Paris Brain Institute - ICM, Inserm, CNRS, Paris, France
| | - David Devos
- The French Ns-Park Network, Paris, France
- Parkinson's Disease Centre of Excellence, Department of Medical Pharmacology, Univ. Lille, INSERM; CHU Lille, U1172 - Degenerative & Vascular Cognitive Disorders, LICEND, NS-Park Network, F-59000, Lille, France
| | - Gwendoline Dupont
- The French Ns-Park Network, Paris, France
- Centre hospitalier universitaire François Mitterrand, Département de Neurologie, Université de Bourgogne, Dijon, France
| | - Matthieu Bereau
- The French Ns-Park Network, Paris, France
- Service de neurologie, université de Franche-Comté, CHRU de Besançon, 25030, Besançon, France
| | - Margherita Fabbri
- The French Ns-Park Network, Paris, France.
- Department of Neurosciences, Clinical Investigation Center CIC 1436, Parkinson Toulouse Expert Centre, NS-Park/FCRIN Network and NeuroToul COEN Center, Toulouse University Hospital, INSERM, University of Toulouse 3, Toulouse, France.
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Tam W, Alajlani M, Abd-Alrazaq A. An Exploration of Wearable Device Features Used in UK Hospital Parkinson Disease Care: Scoping Review. J Med Internet Res 2023; 25:e42950. [PMID: 37594791 PMCID: PMC10474516 DOI: 10.2196/42950] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 03/13/2023] [Accepted: 04/14/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND The prevalence of Parkinson disease (PD) is becoming an increasing concern owing to the aging population in the United Kingdom. Wearable devices have the potential to improve the clinical care of patients with PD while reducing health care costs. Consequently, exploring the features of these wearable devices is important to identify the limitations and further areas of investigation of how wearable devices are currently used in clinical care in the United Kingdom. OBJECTIVE In this scoping review, we aimed to explore the features of wearable devices used for PD in hospitals in the United Kingdom. METHODS A scoping review of the current research was undertaken and reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The literature search was undertaken on June 6, 2022, and publications were obtained from MEDLINE or PubMed, Embase, and the Cochrane Library. Eligible publications were initially screened by their titles and abstracts. Publications that passed the initial screening underwent a full review. The study characteristics were extracted from the final publications, and the evidence was synthesized using a narrative approach. Any queries were reviewed by the first and second authors. RESULTS Of the 4543 publications identified, 39 (0.86%) publications underwent a full review, and 20 (0.44%) publications were included in the scoping review. Most studies (11/20, 55%) were conducted at the Newcastle upon Tyne Hospitals NHS Foundation Trust, with sample sizes ranging from 10 to 418. Most study participants were male individuals with a mean age ranging from 57.7 to 78.0 years. The AX3 was the most popular device brand used, and it was commercially manufactured by Axivity. Common wearable device types included body-worn sensors, inertial measurement units, and smartwatches that used accelerometers and gyroscopes to measure the clinical features of PD. Most wearable device primary measures involved the measured gait, bradykinesia, and dyskinesia. The most common wearable device placements were the lumbar region, head, and wrist. Furthermore, 65% (13/20) of the studies used artificial intelligence or machine learning to support PD data analysis. CONCLUSIONS This study demonstrated that wearable devices could help provide a more detailed analysis of PD symptoms during the assessment phase and personalize treatment. Using machine learning, wearable devices could differentiate PD from other neurodegenerative diseases. The identified evidence gaps include the lack of analysis of wearable device cybersecurity and data management. The lack of cost-effectiveness analysis and large-scale participation in studies resulted in uncertainty regarding the feasibility of the widespread use of wearable devices. The uncertainty around the identified research gaps was further exacerbated by the lack of medical regulation of wearable devices for PD, particularly in the United Kingdom where regulations were changing due to the political landscape.
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Affiliation(s)
- William Tam
- Insitute of Digital Healthcare, Warwick Manufacturing Group, University of Warwick, Coventry, United Kingdom
| | - Mohannad Alajlani
- Insitute of Digital Healthcare, Warwick Manufacturing Group, University of Warwick, Coventry, United Kingdom
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Yen JM, Lim JH. A Clinical Perspective on Bespoke Sensing Mechanisms for Remote Monitoring and Rehabilitation of Neurological Diseases: Scoping Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:536. [PMID: 36617134 PMCID: PMC9823649 DOI: 10.3390/s23010536] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Revised: 12/17/2022] [Accepted: 12/29/2022] [Indexed: 06/17/2023]
Abstract
Neurological diseases including stroke and neurodegenerative disorders cause a hefty burden on the healthcare system. Survivors experience significant impairment in mobility and daily activities, which requires extensive rehabilitative interventions to assist them to regain lost skills and restore independence. The advent of remote rehabilitation architecture and enabling technology mandates the elaboration of sensing mechanisms tailored to individual clinical needs. This study aims to review current trends in the application of sensing mechanisms in remote monitoring and rehabilitation in neurological diseases, and to provide clinical insights to develop bespoke sensing mechanisms. A systematic search was performed using the PubMED database to identify 16 papers published for the period between 2018 to 2022. Teleceptive sensors (56%) were utilized more often than wearable proximate sensors (50%). The most commonly used modality was infrared (38%) and acceleration force (38%), followed by RGB color, EMG, light and temperature, and radio signal. The strategy adopted to improve the sensing mechanism included a multimodal sensor, the application of multiple sensors, sensor fusion, and machine learning. Most of the stroke studies utilized biofeedback control systems (78%) while the majority of studies for neurodegenerative disorders used sensors for remote monitoring (57%). Functional assessment tools that the sensing mechanism may emulate to produce clinically valid information were proposed and factors affecting user adoption were described. Lastly, the limitations and directions for further development were discussed.
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Affiliation(s)
- Jia Min Yen
- Division of Rehabilitation Medicine, University Medicine Cluster, National University Hospital, Singapore 119074, Singapore
| | - Jeong Hoon Lim
- Division of Rehabilitation Medicine, University Medicine Cluster, National University Hospital, Singapore 119074, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore
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Xu Z, Shen B, Tang Y, Wu J, Wang J. Deep Clinical Phenotyping of Parkinson's Disease: Towards a New Era of Research and Clinical Care. PHENOMICS (CHAM, SWITZERLAND) 2022; 2:349-361. [PMID: 36939759 PMCID: PMC9590510 DOI: 10.1007/s43657-022-00051-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 03/12/2022] [Accepted: 03/28/2022] [Indexed: 11/27/2022]
Abstract
Despite recent advances in technology, clinical phenotyping of Parkinson's disease (PD) has remained relatively limited as current assessments are mainly based on empirical observation and subjective categorical judgment at the clinic. A lack of comprehensive, objective, and quantifiable clinical phenotyping data has hindered our capacity to diagnose, assess patients' conditions, discover pathogenesis, identify preclinical stages and clinical subtypes, and evaluate new therapies. Therefore, deep clinical phenotyping of PD patients is a necessary step towards understanding PD pathology and improving clinical care. In this review, we present a growing community consensus and perspective on how to clinically phenotype this disease, that is, to phenotype the entire course of disease progression by integrating capacity, performance, and perception approaches with state-of-the-art technology. We also explore the most studied aspects of PD deep clinical phenotypes, namely, bradykinesia, tremor, dyskinesia and motor fluctuation, gait impairment, speech impairment, and non-motor phenotypes.
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Affiliation(s)
- Zhiheng Xu
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, 200040 China
| | - Bo Shen
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, 200040 China
| | - Yilin Tang
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, 200040 China
| | - Jianjun Wu
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, 200040 China
| | - Jian Wang
- Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, 200040 China
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Tam W, Alajlani M, Abd-alrazaq A. An Exploration of Wearable Device Features Used in UK Hospital Parkinson Disease Care: Scoping Review (Preprint).. [DOI: 10.2196/preprints.42950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
BACKGROUND
The prevalence of Parkinson disease (PD) is becoming an increasing concern owing to the aging population in the United Kingdom. Wearable devices have the potential to improve the clinical care of patients with PD while reducing health care costs. Consequently, exploring the features of these wearable devices is important to identify the limitations and further areas of investigation of how wearable devices are currently used in clinical care in the United Kingdom.
OBJECTIVE
In this scoping review, we aimed to explore the features of wearable devices used for PD in hospitals in the United Kingdom.
METHODS
A scoping review of the current research was undertaken and reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The literature search was undertaken on June 6, 2022, and publications were obtained from MEDLINE or PubMed, Embase, and the Cochrane Library. Eligible publications were initially screened by their titles and abstracts. Publications that passed the initial screening underwent a full review. The study characteristics were extracted from the final publications, and the evidence was synthesized using a narrative approach. Any queries were reviewed by the first and second authors.
RESULTS
Of the 4543 publications identified, 39 (0.86%) publications underwent a full review, and 20 (0.44%) publications were included in the scoping review. Most studies (11/20, 55%) were conducted at the Newcastle upon Tyne Hospitals NHS Foundation Trust, with sample sizes ranging from 10 to 418. Most study participants were male individuals with a mean age ranging from 57.7 to 78.0 years. The AX3 was the most popular device brand used, and it was commercially manufactured by Axivity. Common wearable device types included body-worn sensors, inertial measurement units, and smartwatches that used accelerometers and gyroscopes to measure the clinical features of PD. Most wearable device primary measures involved the measured gait, bradykinesia, and dyskinesia. The most common wearable device placements were the lumbar region, head, and wrist. Furthermore, 65% (13/20) of the studies used artificial intelligence or machine learning to support PD data analysis.
CONCLUSIONS
This study demonstrated that wearable devices could help provide a more detailed analysis of PD symptoms during the assessment phase and personalize treatment. Using machine learning, wearable devices could differentiate PD from other neurodegenerative diseases. The identified evidence gaps include the lack of analysis of wearable device cybersecurity and data management. The lack of cost-effectiveness analysis and large-scale participation in studies resulted in uncertainty regarding the feasibility of the widespread use of wearable devices. The uncertainty around the identified research gaps was further exacerbated by the lack of medical regulation of wearable devices for PD, particularly in the United Kingdom where regulations were changing due to the political landscape.
CLINICALTRIAL
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Rodríguez-Martín D, Cabestany J, Pérez-López C, Pie M, Calvet J, Samà A, Capra C, Català A, Rodríguez-Molinero A. A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ON TM. Front Neurol 2022; 13:912343. [PMID: 35720090 PMCID: PMC9202426 DOI: 10.3389/fneur.2022.912343] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 04/22/2022] [Indexed: 11/13/2022] Open
Abstract
In the past decade, the use of wearable medical devices has been a great breakthrough in clinical practice, trials, and research. In the Parkinson's disease field, clinical evaluation is time limited, and healthcare professionals need to rely on retrospective data collected through patients' self-filled diaries and administered questionnaires. As this often leads to inaccurate evaluations, a more objective system for symptom monitoring in a patient's daily life is claimed. In this regard, the use of wearable medical devices is crucial. This study aims at presenting a review on STAT-ONTM, a wearable medical device Class IIa, which provides objective information on the distribution and severity of PD motor symptoms in home environments. The sensor analyzes inertial signals, with a set of validated machine learning algorithms running in real time. The device was developed for 12 years, and this review aims at gathering all the results achieved within this time frame. First, a compendium of the complete journey of STAT-ONTM since 2009 is presented, encompassing different studies and developments in funded European and Spanish national projects. Subsequently, the methodology of database construction and machine learning algorithms design and development is described. Finally, clinical validation and external studies of STAT-ONTM are presented.
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Affiliation(s)
| | - Joan Cabestany
- Technical Research Centre for Dependency Care and Autonomous Living, Universitat Politecnica de Catalunya, Barcelona, Spain
| | - Carlos Pérez-López
- Department of Investigation, Consorci Sanitari Alt Penedès - Garraf, Vilanova i la Geltrú, Spain
| | - Marti Pie
- Sense4Care S.L., Cornellà de Llobregat, Spain
| | - Joan Calvet
- Sense4Care S.L., Cornellà de Llobregat, Spain
| | - Albert Samà
- Sense4Care S.L., Cornellà de Llobregat, Spain
| | | | - Andreu Català
- Technical Research Centre for Dependency Care and Autonomous Living, Universitat Politecnica de Catalunya, Barcelona, Spain
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Hadley AJ, Riley DE, Heldman DA. Real-World Evidence for a Smartwatch-Based Parkinson's Motor Assessment App for Patients Undergoing Therapy Changes. Digit Biomark 2021; 5:206-215. [PMID: 34703975 DOI: 10.1159/000518571] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 07/19/2021] [Indexed: 01/18/2023] Open
Abstract
Introduction Parkinson's disease (PD) is poorly quantified by patients outside the clinic, and paper diaries have problems with subjective descriptions and bias. Wearable sensor platforms; however, can accurately quantify symptoms such as tremor, dyskinesia, and bradykinesia. Commercially available smartwatches are equipped with accelerometers and gyroscopes that can measure motion for objective evaluation. We sought to evaluate the clinical utility of a prescription smartwatch-based monitoring system for PD utilizing periodic task-based motor assessment. Methods Sixteen patients with PD used a smartphone- and smartwatch-based monitoring system to objectively assess motor symptoms for 1 week prior to instituting a doctor recommended change in therapy and for 4 weeks after the change. After 5 weeks the participants returned to the clinic to discuss their results with their doctor, who made therapy recommendations based on the reports and his clinical judgment. Symptom scores were synchronized with the medication diary and the temporal effects of therapy on weekly and hourly timescales were calculated. Results Thirteen participants successfully completed the study and averaged 4.9 assessments per day for 3 days per week during the study. The doctor instructed 8 participants to continue their new regimens and 5 to revert to their previous regimens. The smartwatch-based assessments successfully captured intraday fluctuations and short- and long-term responses to therapies, including detecting significant improvements (p < 0.05) in at least one symptom in 7 participants. Conclusions The smartwatch-based app successfully captured temporal trends in symptom scores following application of new therapy on hourly, daily, and weekly timescales. These results suggest that validated smartwatch-based PD monitoring can provide clinically relevant information and may reduce the need for traditional office visits for therapy adjustment.
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