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Yang YY, Ho MY, Tai CH, Wu RM, Kuo MC, Tseng YJ. FastEval Parkinsonism: an instant deep learning-assisted video-based online system for Parkinsonian motor symptom evaluation. NPJ Digit Med 2024; 7:31. [PMID: 38332372 PMCID: PMC10853559 DOI: 10.1038/s41746-024-01022-x] [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: 09/27/2023] [Accepted: 01/18/2024] [Indexed: 02/10/2024] Open
Abstract
The Motor Disorder Society's Unified Parkinson's Disease Rating Scale (MDS-UPDRS) is designed to assess bradykinesia, the cardinal symptoms of Parkinson's disease (PD). However, it cannot capture the all-day variability of bradykinesia outside the clinical environment. Here, we introduce FastEval Parkinsonism ( https://fastevalp.cmdm.tw/ ), a deep learning-driven video-based system, providing users to capture keypoints, estimate the severity, and summarize in a report. Leveraging 840 finger-tapping videos from 186 individuals (103 patients with Parkinson's disease (PD), 24 participants with atypical parkinsonism (APD), 12 elderly with mild parkinsonism signs (MPS), and 47 healthy controls (HCs)), we employ a dilated convolution neural network with two data augmentation techniques. Our model achieves acceptable accuracies (AAC) of 88.0% and 81.5%. The frequency-intensity (FI) value of thumb-index finger distance was indicated as a pivotal hand parameter to quantify the performance. Our model also shows the usability for multi-angle videos, tested in an external database enrolling over 300 PD patients.
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Affiliation(s)
- Yu-Yuan Yang
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1 Roosevelt Rd. Sec. 4, Taipei, 10617, Taiwan, ROC
| | - Ming-Yang Ho
- Department of Computer Science and Information Engineering, National Taiwan University, No. 1 Roosevelt Rd. Sec. 4, Taipei, 10617, Taiwan, ROC
| | - Chung-Hwei Tai
- Department of Neurology, National Taiwan University Hospital, No. 1 Changde St., Zhongzheng Dist., Taipei City, 100229, Taiwan, ROC
| | - Ruey-Meei Wu
- Department of Medicine, National Taiwan University Cancer Center, No. 57, Lane 155, Sec. 3, Keelung Rd., Da'an Dist., Taipei City, 106, Taiwan, ROC
| | - Ming-Che Kuo
- Department of Neurology, National Taiwan University Hospital, No. 1 Changde St., Zhongzheng Dist., Taipei City, 100229, Taiwan, ROC.
- Department of Medicine, National Taiwan University Cancer Center, No. 57, Lane 155, Sec. 3, Keelung Rd., Da'an Dist., Taipei City, 106, Taiwan, ROC.
| | - Yufeng Jane Tseng
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1 Roosevelt Rd. Sec. 4, Taipei, 10617, Taiwan, ROC.
- Department of Computer Science and Information Engineering, National Taiwan University, No. 1 Roosevelt Rd. Sec. 4, Taipei, 10617, Taiwan, ROC.
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Virmani T, Kemp AS, Pillai L, Glover A, Spencer H, Larson-Prior L. Development and implementation of the frog-in-maze game to study upper limb movement in people with Parkinson's disease. Sci Rep 2023; 13:22784. [PMID: 38123606 PMCID: PMC10733393 DOI: 10.1038/s41598-023-49382-w] [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: 02/21/2023] [Accepted: 12/07/2023] [Indexed: 12/23/2023] Open
Abstract
Upper-limb bradykinesia occurs early in Parkinson's disease (PD) and bradykinesia is required for diagnosis. Our goal was to develop, implement and validate a game "walking" a frog through a maze using bimanual, alternating finger-tapping movements to provide a salient, objective, and remotely monitorable method of tracking disease progression and response to therapy in PD. Twenty-five people with PD and 16 people without PD participated. Responses on 5 different mazes were quantified and compared to spatiotemporal gait parameters and standard disease metrics in these participants. Intertap interval (ITI) on maze 2 & 3, which included turns, was strongly inversely related to stride-length and stride-velocity and directly related to motor UPDRS scores. Levodopa decreased ITI, except in maze 4. PD participants with freezing of gait had longer ITI on all mazes. The responses quantified on maze 2 & 3 were related to disease severity and gait stride-length, were levodopa responsive, and were worse in people with freezing of gait, suggesting that these mazes could be used to quantify motor dysfunction in PD. Programming our frog-in-maze game onto a remotely distributable platform could provide a tool to monitor disease progression and therapeutic response in people with PD, including during clinical trials.
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Affiliation(s)
- Tuhin Virmani
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, 4301 W. Markham St., #500, Little Rock, AR, 72205, USA.
- Department of Neurology, University of Arkansas for Medical Sciences, 4301 W. Markham St., #500, Little Rock, AR, 72205, USA.
| | - Aaron S Kemp
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, 4301 W. Markham St., #500, Little Rock, AR, 72205, USA
| | - Lakshmi Pillai
- Department of Neurology, University of Arkansas for Medical Sciences, 4301 W. Markham St., #500, Little Rock, AR, 72205, USA
| | - Aliyah Glover
- Department of Neurology, University of Arkansas for Medical Sciences, 4301 W. Markham St., #500, Little Rock, AR, 72205, USA
| | - Horace Spencer
- Department of Biostatistics, University of Arkansas for Medical Sciences, 4301 W. Markham St., #500, Little Rock, AR, 72205, USA
| | - Linda Larson-Prior
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, 4301 W. Markham St., #500, Little Rock, AR, 72205, USA
- Department of Neurology, University of Arkansas for Medical Sciences, 4301 W. Markham St., #500, Little Rock, AR, 72205, USA
- Department of Neurobiology, University of Arkansas for Medical Sciences, 4301 W. Markham St., #500, Little Rock, AR, 72205, USA
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Jha A, Espay AJ, Lees AJ. Digital Biomarkers in Parkinson's Disease: Missing the Forest for the Trees? Mov Disord Clin Pract 2023; 10:S68-S72. [PMID: 37637991 PMCID: PMC10448130 DOI: 10.1002/mdc3.13746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/21/2023] [Accepted: 03/29/2023] [Indexed: 08/29/2023] Open
Affiliation(s)
- Ashwani Jha
- UCL Queen Square Institute of NeurologyLondonUnited Kingdom
| | - Alberto J. Espay
- James J. and Joan A. Gardner Family Center for Parkinson's Disease and Movement Disorders, Department of NeurologyUniversity of CincinnatiCincinnatiOhioUSA
| | - Andrew J. Lees
- Reta Lila Weston Institute of Neurological Studies, Department of Clinical Movement Disorder and Neuroscience, Institute of NeurologyUniversity College LondonLondonUnited Kingdom
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Mammen JR, Speck RM, Stebbins GM, Müller MLTM, Yang PT, Campbell M, Cosman J, Crawford JE, Dam T, Hellsten J, Jensen-Roberts S, Kostrzebski M, Simuni T, Barowicz KW, Cedarbaum JM, Dorsey ER, Stephenson D, Adams JL. Mapping Relevance of Digital Measures to Meaningful Symptoms and Impacts in Early Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2023:JPD225122. [PMID: 37212073 DOI: 10.3233/jpd-225122] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
BACKGROUND Adoption of new digital measures for clinical trials and practice has been hindered by lack of actionable qualitative data demonstrating relevance of these metrics to people with Parkinson's disease. OBJECTIVE This study evaluated of relevance of WATCH-PD digital measures to meaningful symptoms and impacts of early Parkinson's disease from the patient perspective. METHODS Participants with early Parkinson's disease (N = 40) completed surveys and 1:1 online-interviews. Interviews combined: 1) symptom mapping to delineate meaningful symptoms/impacts of disease, 2) cognitive interviewing to assess content validity of digital measures, and 3) mapping of digital measures back to personal symptoms to assess relevance from the patient perspective. Content analysis and descriptive techniques were used to analyze data. RESULTS Participants perceived mapping as deeply engaging, with 39/40 reporting improved ability to communicate important symptoms and relevance of measures. Most measures (9/10) were rated relevant by both cognitive interviewing (70-92.5%) and mapping (80-100%). Two measures related to actively bothersome symptoms for more than 80% of participants (Tremor, Shape rotation). Tasks were generally deemed relevant if they met three participant context criteria: 1) understanding what the task measured, 2) believing it targeted an important symptom of PD (past, present, or future), and 3) believing the task was a good test of that important symptom. Participants did not require that a task relate to active symptoms or "real" life to be relevant. CONCLUSION Digital measures of tremor and hand dexterity were rated most relevant in early PD. Use of mapping enabled precise quantification of qualitative data for more rigorous evaluation of new measures.
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Affiliation(s)
| | | | - Glenn M Stebbins
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | | | - Phillip T Yang
- Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA
| | - Michelle Campbell
- Center for Drug Evaluation and Research (CDER), U.S. Food and Drug Administration (FDA), Silver Spring, MD, USA
| | | | | | | | | | - Stella Jensen-Roberts
- Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA
| | - Melissa Kostrzebski
- Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA
- Department of Neurology, University of Rochester, Medical Center, Rochester, NY, USA
| | - Tanya Simuni
- Northwestern University Feinberg School of Medicine, Chicago IL, USA
| | | | - Jesse M Cedarbaum
- Coeruleus Clinical Sciences LLC, Woodbridge, CT, USA
- Yale Medical School, New Haven, CT, USA
| | - E Ray Dorsey
- Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA
- Department of Neurology, University of Rochester, Medical Center, Rochester, NY, USA
| | | | - Jamie L Adams
- Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA
- Department of Neurology, University of Rochester, Medical Center, Rochester, NY, USA
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5
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Gonzalez-Robles C, Weil RS, van Wamelen D, Bartlett M, Burnell M, Clarke CS, Hu MT, Huxford B, Jha A, Lambert C, Lawton M, Mills G, Noyce A, Piccini P, Pushparatnam K, Rochester L, Siu C, Williams-Gray CH, Zeissler ML, Zetterberg H, Carroll CB, Foltynie T, Schrag A. Outcome Measures for Disease-Modifying Trials in Parkinson's Disease: Consensus Paper by the EJS ACT-PD Multi-Arm Multi-Stage Trial Initiative. JOURNAL OF PARKINSON'S DISEASE 2023; 13:1011-1033. [PMID: 37545260 PMCID: PMC10578294 DOI: 10.3233/jpd-230051] [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: 06/23/2023] [Indexed: 08/08/2023]
Abstract
BACKGROUND Multi-arm, multi-stage (MAMS) platform trials can accelerate the identification of disease-modifying treatments for Parkinson's disease (PD) but there is no current consensus on the optimal outcome measures (OM) for this approach. OBJECTIVE To provide an up-to-date inventory of OM for disease-modifying PD trials, and a framework for future selection of OM for such trials. METHODS As part of the Edmond J Safra Accelerating Clinical Trials in Parkinson Disease (EJS ACT-PD) initiative, an expert group with Patient and Public Involvement and Engagement (PPIE) representatives' input reviewed and evaluated available evidence on OM for potential use in trials to delay progression of PD. Each OM was ranked based on aspects such as validity, sensitivity to change, participant burden and practicality for a multi-site trial. Review of evidence and expert opinion led to the present inventory. RESULTS An extensive inventory of OM was created, divided into: general, motor and non-motor scales, diaries and fluctuation questionnaires, cognitive, disability and health-related quality of life, capability, quantitative motor, wearable and digital, combined, resource use, imaging and wet biomarkers, and milestone-based. A framework for evaluation of OM is presented to update the inventory in the future. PPIE input highlighted the need for OM which reflect their experience of disease progression and are applicable to diverse populations and disease stages. CONCLUSION We present a range of OM, classified according to a transparent framework, to aid selection of OM for disease-modifying PD trials, whilst allowing for inclusion or re-classification of relevant OM as new evidence emerges.
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Affiliation(s)
| | | | | | | | - Matthew Burnell
- Medical Research Council Clinical Trials Unit at University College London, London, UK
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Lipsmeier F, Taylor KI, Postuma RB, Volkova-Volkmar E, Kilchenmann T, Mollenhauer B, Bamdadian A, Popp WL, Cheng WY, Zhang YP, Wolf D, Schjodt-Eriksen J, Boulay A, Svoboda H, Zago W, Pagano G, Lindemann M. Reliability and validity of the Roche PD Mobile Application for remote monitoring of early Parkinson's disease. Sci Rep 2022; 12:12081. [PMID: 35840753 PMCID: PMC9287320 DOI: 10.1038/s41598-022-15874-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 06/30/2022] [Indexed: 11/19/2022] Open
Abstract
Digital health technologies enable remote and therefore frequent measurement of motor signs, potentially providing reliable and valid estimates of motor sign severity and progression in Parkinson’s disease (PD). The Roche PD Mobile Application v2 was developed to measure bradykinesia, bradyphrenia and speech, tremor, gait and balance. It comprises 10 smartphone active tests (with ½ tests administered daily), as well as daily passive monitoring via a smartphone and smartwatch. It was studied in 316 early-stage PD participants who performed daily active tests at home then carried a smartphone and wore a smartwatch throughout the day for passive monitoring (study NCT03100149). Here, we report baseline data. Adherence was excellent (96.29%). All pre-specified sensor features exhibited good-to-excellent test–retest reliability (median intraclass correlation coefficient = 0.9), and correlated with corresponding Movement Disorder Society–Unified Parkinson's Disease Rating Scale items (rho: 0.12–0.71). These findings demonstrate the preliminary reliability and validity of remote at-home quantification of motor sign severity with the Roche PD Mobile Application v2 in individuals with early PD.
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Affiliation(s)
- Florian Lipsmeier
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Kirsten I Taylor
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Ronald B Postuma
- Department of Neurology, McGill University, Montreal General Hospital, Montreal, QC, Canada
| | - Ekaterina Volkova-Volkmar
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Timothy Kilchenmann
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Brit Mollenhauer
- Paracelsus-Elena-Klinik, Kassel, Germany.,Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
| | - Atieh Bamdadian
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Werner L Popp
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Wei-Yi Cheng
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Yan-Ping Zhang
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Detlef Wolf
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Jens Schjodt-Eriksen
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Anne Boulay
- Idorsia Pharmaceuticals Ltd, Allschwil, Switzerland
| | - Hanno Svoboda
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Wagner Zago
- Prothena Biosciences Inc, South San Francisco, CA, USA
| | - Gennaro Pagano
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Michael Lindemann
- Roche Pharma Research and Early Development, pRED Informatics, Pharmaceutical Sciences, Clinical Pharmacology, and Neuroscience and Rare Diseases Discovery and Translational Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, 4070, Basel, Switzerland
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7
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Gopal A, Hsu WY, Allen DD, Bove R. Remote Assessments of Hand Function in Neurological Disorders: Systematic Review. JMIR Rehabil Assist Technol 2022; 9:e33157. [PMID: 35262502 PMCID: PMC8943610 DOI: 10.2196/33157] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 01/17/2022] [Accepted: 01/26/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Loss of fine motor skills is observed in many neurological diseases, and remote monitoring assessments can aid in early diagnosis and intervention. Hand function can be regularly assessed to monitor loss of fine motor skills in people with central nervous system disorders; however, there are challenges to in-clinic assessments. Remotely assessing hand function could facilitate monitoring and supporting of early diagnosis and intervention when warranted. OBJECTIVE Remote assessments can facilitate the tracking of limitations, aiding in early diagnosis and intervention. This study aims to systematically review existing evidence regarding the remote assessment of hand function in populations with chronic neurological dysfunction. METHODS PubMed and MEDLINE, CINAHL, Web of Science, and Embase were searched for studies that reported remote assessment of hand function (ie, outside of traditional in-person clinical settings) in adults with chronic central nervous system disorders. We excluded studies that included participants with orthopedic upper limb dysfunction or used tools for intervention and treatment. We extracted data on the evaluated hand function domains, validity and reliability, feasibility, and stage of development. RESULTS In total, 74 studies met the inclusion criteria for Parkinson disease (n=57, 77% studies), stroke (n=9, 12%), multiple sclerosis (n=6, 8%), spinal cord injury (n=1, 1%), and amyotrophic lateral sclerosis (n=1, 1%). Three assessment modalities were identified: external device (eg, wrist-worn accelerometer), smartphone or tablet, and telerehabilitation. The feasibility and overall participant acceptability were high. The most common hand function domains assessed included finger tapping speed (fine motor control and rigidity), hand tremor (pharmacological and rehabilitation efficacy), and finger dexterity (manipulation of small objects required for daily tasks) and handwriting (coordination). Although validity and reliability data were heterogeneous across studies, statistically significant correlations with traditional in-clinic metrics were most commonly reported for telerehabilitation and smartphone or tablet apps. The most readily implementable assessments were smartphone or tablet-based. CONCLUSIONS The findings show that remote assessment of hand function is feasible in neurological disorders. Although varied, the assessments allow clinicians to objectively record performance in multiple hand function domains, improving the reliability of traditional in-clinic assessments. Remote assessments, particularly via telerehabilitation and smartphone- or tablet-based apps that align with in-clinic metrics, facilitate clinic to home transitions, have few barriers to implementation, and prompt remote identification and treatment of hand function impairments.
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Affiliation(s)
- Arpita Gopal
- Weill Institute of Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Wan-Yu Hsu
- Weill Institute of Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Diane D Allen
- Department of Physical Therapy and Rehabilitation Science, University of California San Francisco/San Francisco State University, San Francisco, CA, United States
| | - Riley Bove
- Weill Institute of Neurosciences, University of California San Francisco, San Francisco, CA, United States
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Abstract
Internet-connected devices, including personal computers, smartphones, smartwatches, and voice assistants, have evolved into powerful multisensor technologies that billions of people interact with daily to connect with friends and colleagues, access and share information, purchase goods, play games, and navigate their environment. Digital phenotyping taps into the data streams captured by these devices to characterize and understand health and disease. The purpose of this article is to summarize opportunities for digital phenotyping in neurology, review studies using everyday technologies to obtain motor and cognitive information, and provide a perspective on how neurologists can embrace and accelerate progress in this emerging field.
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Affiliation(s)
- Anoopum S. Gupta
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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9
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James-Palmer AM, Daneault JF. Tele-yoga for the management of Parkinson disease: A safety and feasibility trial. Digit Health 2022; 8:20552076221119327. [PMID: 35990111 PMCID: PMC9386843 DOI: 10.1177/20552076221119327] [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: 06/29/2022] [Accepted: 05/30/2022] [Indexed: 11/22/2022] Open
Abstract
Objectives Despite current standard treatments, persons with Parkinson disease (PD) still experience motor and non-motor symptoms that impact daily function and quality of life, warranting the investigation of additional interventions. Holistic complementary interventions such as yoga have been shown to be beneficial for persons with PD. However, there are multiple barriers to in-person interventions such as transportation difficulties and disease-related mobility impairments which may be mitigated by digital health applications. Therefore, this study’s purpose was to assess the safety and feasibility of a synchronous tele-yoga intervention for persons with PD. Methods Sixteen participants were enrolled in a single group safety and feasibility trial. The entire study was conducted remotely and consisted of a baseline assessment followed by a six-week waiting period, then a second assessment, a six-week tele-yoga intervention period, a post-intervention assessment, a six-week follow-up period, and lastly a follow-up assessment. During the tele-yoga period, participants completed two one-on-one 30-minute tele-yoga sessions weekly for a total of 12 sessions. Primary outcomes included adverse events, adherence, technological challenges, and usability. Secondary outcomes included enjoyment and clinically relevant outcome measures assessing both motor and non-motor symptoms. Results No severe adverse events were attributed to the intervention. Retention was 87.5%, assessment session adherence was 100%, and intervention session adherence was 97%. Technological challenges did not impact feasibility. The intervention was usable and enjoyable. While this study was not powered or designed to assess the efficacy of the intervention, preliminary improvements were shown for some of the clinically relevant outcome measures. Conclusions Overall, this study showed that the implementation of a synchronous one-on-one tele-yoga intervention was safe, feasible, usable, and enjoyable for persons with PD. Randomized control trials investigating its efficacy should be initiated. The study was registered with ClinicalTrials.gov (NCT04240899, https://clinicaltrials.gov/ct2/show/NCT04240899).
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Affiliation(s)
- Aurora M James-Palmer
- Department of Rehabilitation and Movement Sciences, Rutgers University, Newark, NJ, USA
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10
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Stamate C, Saez Pons J, Weston D, Roussos G. PDKit: A data science toolkit for the digital assessment of Parkinson's Disease. PLoS Comput Biol 2021; 17:e1008833. [PMID: 33711008 PMCID: PMC7990207 DOI: 10.1371/journal.pcbi.1008833] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 03/24/2021] [Accepted: 02/24/2021] [Indexed: 01/05/2023] Open
Abstract
PDkit is an open source software toolkit supporting the collaborative development of novel methods of digital assessment for Parkinson’s Disease, using symptom measurements captured continuously by wearables (passive monitoring) or by high-use-frequency smartphone apps (active monitoring). The goal of the toolkit is to help address the current lack of algorithmic and model transparency in this area by facilitating open sharing of standardised methods that allow the comparison of results across multiple centres and hardware variations. PDkit adopts the information-processing pipeline abstraction incorporating stages for data ingestion, quality of information augmentation, feature extraction, biomarker estimation and finally, scoring using standard clinical scales. Additionally, a dataflow programming framework is provided to support high performance computations. The practical use of PDkit is demonstrated in the context of the CUSSP clinical trial in the UK. The toolkit is implemented in the python programming language, the de facto standard for modern data science applications, and is widely available under the MIT license. Parkinson’s Disease is the fastest growing neurological condition affecting millions of people across the world. People with Parkinson’s suffer from a variety of symptoms that result in diminished ability to move, eat, remember or sleep. Research in new treatments are limited because the clinical tools used to assess its symptoms are subjective, require considerable time to perform and specialised skills and can only detect coarse-grain changes. To address this situation, clinicians are turning to smartphone apps and wearables to create new ways to assess symptoms that are more sensitive to change and can be applied frequently at home by patients and their carers. In this paper, we discuss PDkit, an open source toolkit that we developed to help address this current lack of algorithmic and model transparency. Adopting PDkit facilitates the open sharing of standardised methods and can accelerate the development of new methods and system to assess Parkinson’s and enables research groups to innovate. The toolkit provides funcionality that support data ingestion, quality of information augmentation, feature extraction, biomarker estimation and finally, scoring using standard clinical scales. The practical use of PDkit is demonstrated via its use by the CUSSP clinical trial conducted in the UK.
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Affiliation(s)
- Cosmin Stamate
- Department of Computer Science and Information Systems, Birkbeck College, University of London, London, United Kingdom
| | - Joan Saez Pons
- Department of Computer Science and Information Systems, Birkbeck College, University of London, London, United Kingdom
| | - David Weston
- Department of Computer Science and Information Systems, Birkbeck College, University of London, London, United Kingdom
| | - George Roussos
- Department of Computer Science and Information Systems, Birkbeck College, University of London, London, United Kingdom
- * E-mail:
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