Literature DB >> 33523020

Body-Worn Sensors for Remote Monitoring of Parkinson's Disease Motor Symptoms: Vision, State of the Art, and Challenges Ahead.

Silvia Del Din1, Cameron Kirk1, Alison J Yarnall1,2, Lynn Rochester1,2, Jeffrey M Hausdorff3,4,5.   

Abstract

The increasing prevalence of neurodegenerative conditions such as Parkinson's disease (PD) and related mobility issues places a serious burden on healthcare systems. The COVID-19 pandemic has reinforced the urgent need for better tools to manage chronic conditions remotely, as regular access to clinics may be problematic. Digital health technology in the form of remote monitoring with body-worn sensors offers significant opportunities for transforming research and revolutionizing the clinical management of PD. Significant efforts are being invested in the development and validation of digital outcomes to support diagnosis and track motor and mobility impairments "off-line". Imagine being able to remotely assess your patient, understand how well they are functioning, evaluate the impact of any recent medication/intervention, and identify the need for urgent follow-up before overt, irreparable change takes place? This could offer new pragmatic solutions for personalized care and clinical research. So the question remains: how close are we to achieving this? Here, we describe the state-of-the-art based on representative papers published between 2017 and 2020. We focus on remote (i.e., real-world, daily-living) monitoring of PD using body-worn sensors (e.g., accelerometers, inertial measurement units) for assessing motor symptoms and their complications. Despite the tremendous potential, existing challenges exist (e.g., validity, regulatory) that are preventing the widespread clinical adoption of body-worn sensors as a digital outcome. We propose a roadmap with clear recommendations for addressing these challenges and future directions to bring us closer to the implementation and widespread adoption of this important way of improving the clinical care, evaluation, and monitoring of PD.

Entities:  

Keywords:  Parkinson’s disease; accelerometer; motor symptoms; real-world; remote monitoring; wearables

Mesh:

Year:  2021        PMID: 33523020     DOI: 10.3233/JPD-202471

Source DB:  PubMed          Journal:  J Parkinsons Dis        ISSN: 1877-7171            Impact factor:   5.568


  12 in total

1.  Home-Based Measurements of Dystonia in Cerebral Palsy Using Smartphone-Coupled Inertial Sensor Technology and Machine Learning: A Proof-of-Concept Study.

Authors:  Dylan den Hartog; Marjolein M van der Krogt; Sven van der Burg; Ignazio Aleo; Johannes Gijsbers; Laura A Bonouvrié; Jaap Harlaar; Annemieke I Buizer; Helga Haberfehlner
Journal:  Sensors (Basel)       Date:  2022-06-09       Impact factor: 3.847

2.  Watching Parkinson's disease with wrist-based sensors.

Authors:  James A Diao; Marium M Raza; Kaushik P Venkatesh; Joseph C Kvedar
Journal:  NPJ Digit Med       Date:  2022-06-13

Review 3.  Internet of Things Technologies and Machine Learning Methods for Parkinson's Disease Diagnosis, Monitoring and Management: A Systematic Review.

Authors:  Konstantina-Maria Giannakopoulou; Ioanna Roussaki; Konstantinos Demestichas
Journal:  Sensors (Basel)       Date:  2022-02-24       Impact factor: 3.576

Review 4.  The state of telemedicine for persons with Parkinson's disease.

Authors:  Robin van den Bergh; Bastiaan R Bloem; Marjan J Meinders; Luc J W Evers
Journal:  Curr Opin Neurol       Date:  2021-08-01       Impact factor: 6.283

5.  Effect of Fear of Falling on Mobility Measured During Lab and Daily Activity Assessments in Parkinson's Disease.

Authors:  Arash Atrsaei; Clint Hansen; Morad Elshehabi; Susanne Solbrig; Daniela Berg; Inga Liepelt-Scarfone; Walter Maetzler; Kamiar Aminian
Journal:  Front Aging Neurosci       Date:  2021-11-30       Impact factor: 5.750

Review 6.  Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes.

Authors:  Ashley Polhemus; Laura Delgado Ortiz; Gavin Brittain; Nikolaos Chynkiamis; Francesca Salis; Heiko Gaßner; Michaela Gross; Cameron Kirk; Rachele Rossanigo; Kristin Taraldsen; Diletta Balta; Sofie Breuls; Sara Buttery; Gabriela Cardenas; Christoph Endress; Julia Gugenhan; Alison Keogh; Felix Kluge; Sarah Koch; M Encarna Micó-Amigo; Corinna Nerz; Chloé Sieber; Parris Williams; Ronny Bergquist; Magda Bosch de Basea; Ellen Buckley; Clint Hansen; A Stefanie Mikolaizak; Lars Schwickert; Kirsty Scott; Sabine Stallforth; Janet van Uem; Beatrix Vereijken; Andrea Cereatti; Heleen Demeyer; Nicholas Hopkinson; Walter Maetzler; Thierry Troosters; Ioannis Vogiatzis; Alison Yarnall; Clemens Becker; Judith Garcia-Aymerich; Letizia Leocani; Claudia Mazzà; Lynn Rochester; Basil Sharrack; Anja Frei; Milo Puhan
Journal:  NPJ Digit Med       Date:  2021-10-14

7.  Rapid development of an integrated remote programming platform for neuromodulation systems through the biodesign process.

Authors:  Peter Silburn; Scott DeBates; Tucker Tomlinson; Jeremy Schwark; Gregory Creek; Hiren Patel; Asish Punnoose; Binith Cheeran; Erika Ross; Douglas Lautner; Yagna J Pathak
Journal:  Sci Rep       Date:  2022-02-10       Impact factor: 4.379

8.  Dual-Task Treadmill Training for the Prevention of Falls in Parkinson's Disease: Rationale and Study Design.

Authors:  Veit Mylius; Laura Maes; Katrin Negele; Christine Schmid; Ramona Sylvester; Caroline Sharon Brook; Florian Brugger; Santiago Perez-Lloret; Jens Bansi; Kamiar Aminian; Anisoara Paraschiv-Ionescu; Roman Gonzenbach; Peter Brugger
Journal:  Front Rehabil Sci       Date:  2022-03-02

9.  Predicting Axial Impairment in Parkinson's Disease through a Single Inertial Sensor.

Authors:  Luigi Borzì; Ivan Mazzetta; Alessandro Zampogna; Antonio Suppa; Fernanda Irrera; Gabriella Olmo
Journal:  Sensors (Basel)       Date:  2022-01-06       Impact factor: 3.576

Review 10.  Facilitators and barriers to real-life mobility in community-dwelling older adults: a narrative review of accelerometry- and global positioning system-based studies.

Authors:  Andrea L Rosso; Ervin Sejdić; Anisha Suri; Jessie VanSwearingen; Pamela Dunlap; Mark S Redfern
Journal:  Aging Clin Exp Res       Date:  2022-03-11       Impact factor: 4.481

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