Wearable Solutions for Patients with Parkinson’s Disease and Neurocognitive Disorder: A Systematic Review

Prevalence of neurocognitive diseases in adult patients demands the use of wearable devices to transform the future of mental health. Recent development in wearable technology proclaimed its use in diagnosis, rehabilitation, assessment, and monitoring. This systematic review presents the state of the art of wearables used by Parkinson’s disease (PD) patients or the patients who are going through a neurocognitive disorder. This article is based on PRISMA guidelines, and the literature is searched between January 2009 to January 2020 analyzing four databases: PubMed, IEEE Xplorer, Elsevier, and ISI Web of Science. For further validity of articles, a new PEDro-inspired technique is implemented. In PEDro, five statistical indicators were set to classify relevant articles and later the citations were also considered to make strong assessment of relevant articles. This led to 46 articles that met inclusion criteria. Based on them, this systematic review examines different types of wearable devices, essential in improving early diagnose and monitoring, emphasizing their role in improving the quality of life, differentiating the various fitness and gait wearable-based exercises and their impact on the regression of disease and on the motor diagnosis tests and finally addressing the available wearable insoles and their role in rehabilitation. The research findings proved that sensor based wearable devices, and specially instrumented insoles, help not only in monitoring and diagnosis but also in tracking numerous exercises and their positive impact towards the improvement of quality of life among different Parkinson and neurocognitive patients.

[1]  J. Baker Gait Disorders. , 2018, The American journal of medicine.

[2]  Kenneth McIsaac,et al.  Towards remote monitoring of Parkinson’s disease tremor using wearable motion capture systems , 2018, Journal of the Neurological Sciences.

[3]  Kamiar Aminian,et al.  On-Shoe Wearable Sensors for Gait and Turning Assessment of Patients With Parkinson's Disease , 2013, IEEE Transactions on Biomedical Engineering.

[4]  Taylor Chomiak,et al.  Wearable technological platform for multidomain diagnostic and exercise interventions in Parkinson's disease. , 2019, International review of neurobiology.

[5]  Antoine Piau,et al.  Current State of Digital Biomarker Technologies for Real-Life, Home-Based Monitoring of Cognitive Function for Mild Cognitive Impairment to Mild Alzheimer Disease and Implications for Clinical Care: Systematic Review , 2019, Journal of medical Internet research.

[6]  Jorik Nonnekes,et al.  Multidisciplinary Care to Optimize Functional Mobility in Parkinson Disease. , 2020, Clinics in geriatric medicine.

[7]  Kenneth A. Loparo,et al.  Design and Development of a Smart Exercise Bike for Motor Rehabilitation in Individuals With Parkinson's Disease , 2016, IEEE/ASME Transactions on Mechatronics.

[8]  James McNames,et al.  Using Portable Transducers to Measure Tremor Severity , 2016, Tremor and other hyperkinetic movements.

[9]  Michela Goffredo,et al.  Clinical effects of robot-assisted gait training and treadmill training for Parkinson's disease. A randomized controlled trial. , 2019, Annals of physical and rehabilitation medicine.

[10]  Jerker Westin,et al.  Evaluation of a sensor algorithm for motor state rating in Parkinson's disease. , 2019, Parkinsonism & related disorders.

[11]  F. Cavallo,et al.  How Wearable Sensors Can Support Parkinson's Disease Diagnosis and Treatment: A Systematic Review , 2017, Front. Neurosci..

[12]  Colleen G Canning,et al.  Home-based prescribed exercise improves balance-related activities in people with Parkinson's disease and has benefits similar to centre-based exercise: a systematic review. , 2019, Journal of physiotherapy.

[13]  C. Mazzà,et al.  Free‐living monitoring of Parkinson's disease: Lessons from the field , 2016, Movement disorders : official journal of the Movement Disorder Society.

[14]  Gianluca Bonora,et al.  Wearable Sensor-Based Biofeedback Training for Balance and Gait in Parkinson Disease: A Pilot Randomized Controlled Trial. , 2017, Archives of physical medicine and rehabilitation.

[15]  Jorik Nonnekes,et al.  Clinical and methodological challenges for assessing freezing of gait: Future perspectives , 2019, Movement disorders : official journal of the Movement Disorder Society.

[16]  Heesook Son,et al.  Mobility monitoring using smart technologies for Parkinson’s disease in free-living environment , 2017, Collegian.

[17]  K Aminian,et al.  Technical and clinical view on ambulatory assessment in Parkinson's disease , 2014, Acta neurologica Scandinavica.

[18]  John Dixon,et al.  The effects of prolonged wear of textured shoe insoles on gait, foot sensation and proprioception in people with multiple sclerosis: study protocol for a randomised controlled trial , 2016, Trials.

[19]  Brendan O'Flynn,et al.  Design of a smart insole for ambulatory assessment of gait , 2015, 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN).

[20]  Carlos Balaguer,et al.  Review of Automated Systems for Upper Limbs Functional Assessment in Neurorehabilitation , 2019, IEEE Access.

[21]  Lisbeth Fagerström,et al.  Person-centered home-based rehabilitation for persons with Parkinson's disease: A scoping review. , 2019, International journal of nursing studies.

[22]  Dimitrios I. Fotiadis,et al.  A wearable system for long-term ubiquitous monitoring of common motor symptoms in patients with Parkinson's disease , 2014, IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI).

[23]  Michael Schwenk,et al.  Effects of Wearable Sensor-Based Balance and Gait Training on Balance, Gait, and Functional Performance in Healthy and Patient Populations: A Systematic Review and Meta-Analysis of Randomized Controlled Trials , 2017, Gerontology.

[24]  Bastiaan R. Bloem,et al.  Physiotherapy improves motor function in patients with the Parkinson variant of multiple system atrophy: A prospective trial. , 2019, Parkinsonism & related disorders.

[25]  Joana Figueiredo,et al.  Automatic recognition of gait patterns in human motor disorders using machine learning: A review. , 2018, Medical engineering & physics.

[26]  Laura Rocchi,et al.  Feasibility and effects of home-based smartphone-delivered automated feedback training for gait in people with Parkinson's disease: A pilot randomized controlled trial. , 2016, Parkinsonism & related disorders.

[27]  Julius Griškevičius,et al.  Quantitative Analysis of Parkinsonian Tremor in a Clinical Setting Using Inertial Measurement Units , 2018, Parkinson's disease.

[28]  Cristina Rusu,et al.  A wireless sensor insole for collecting gait data. , 2014, Studies in health technology and informatics.

[29]  Kwang Suk Park,et al.  Wrist sensor-based tremor severity quantification in Parkinson's disease using convolutional neural network , 2018, Comput. Biol. Medicine.

[30]  Kun-Chan Lan,et al.  Early Diagnosis of Parkinson's Disease Using a Smartphone , 2014, FNC/MobiSPC.

[31]  Sinziana Mazilu,et al.  Prediction of Freezing of Gait in Parkinson's From Physiological Wearables: An Exploratory Study , 2015, IEEE Journal of Biomedical and Health Informatics.

[32]  Angelo Antonini,et al.  Wearable sensor-based objective assessment of motor symptoms in Parkinson’s disease , 2015, Journal of Neural Transmission.

[33]  D. Heldman,et al.  Wearable Sensors for Advanced Therapy Referral in Parkinson's Disease. , 2016, Journal of Parkinson's disease.

[34]  Max A. Little,et al.  Machine learning for large‐scale wearable sensor data in Parkinson's disease: Concepts, promises, pitfalls, and futures , 2016, Movement disorders : official journal of the Movement Disorder Society.

[35]  Björn Eskofier,et al.  An Emerging Era in the Management of Parkinson's Disease: Wearable Technologies and the Internet of Things , 2015, IEEE Journal of Biomedical and Health Informatics.

[36]  Ya Wang,et al.  Monitoring Insole (MONI): A Low Power Solution Toward Daily Gait Monitoring and Analysis , 2019, IEEE Sensors Journal.

[37]  G. Avitabile,et al.  A wearable wireless system for gait analysis for early diagnosis of Alzheimer and Parkinson disease , 2016, 2016 5th International Conference on Electronic Devices, Systems and Applications (ICEDSA).

[38]  Jin-Siang Shaw,et al.  Gait Disorders in Parkinson's Disease: Assessment and Management , 2013 .

[39]  Patrick Browne,et al.  A Technological Review of Wearable Cueing Devices Addressing Freezing of Gait in Parkinson’s Disease , 2019, Sensors.

[40]  Kenneth McIsaac,et al.  Quantification of whole-body bradykinesia in Parkinson's disease participants using multiple inertial sensors , 2018, Journal of the Neurological Sciences.

[41]  Victor I. Chang,et al.  Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare , 2018, Future Gener. Comput. Syst..

[42]  Manuela Galli,et al.  Timed Up and Go evaluation with wearable devices: Validation in Parkinson's disease. , 2017, Journal of bodywork and movement therapies.

[43]  Graham K. Kerr,et al.  Effects of Textured Insoles on Balance in People with Parkinson’s Disease , 2013, PloS one.

[44]  Anson B. Rosenfeldt,et al.  Mobility improves after high intensity aerobic exercise in individuals with Parkinson's disease , 2019, Journal of the Neurological Sciences.

[45]  Xiaofeng Wang,et al.  A Self-Powered Insole for Human Motion Recognition , 2016, Sensors.

[46]  Anahita Khojandi,et al.  Optimizing Clinical Assessments in Parkinson's Disease Through the Use of Wearable Sensors and Data Driven Modeling , 2018, Front. Comput. Neurosci..

[47]  David H. Barlow,et al.  Essentials of Abnormal Psychology , 2002 .

[48]  Ghorban Taghizadeh,et al.  The effect of sensory‐motor training on hand and upper extremity sensory and motor function in patients with idiopathic Parkinson disease , 2017, Journal of hand therapy : official journal of the American Society of Hand Therapists.

[49]  Eduardo Rocon,et al.  Smartwatch for the analysis of rest tremor in patients with Parkinson's disease , 2019, Journal of the Neurological Sciences.

[50]  V. Holanda,et al.  Parkinson's disease and wearable devices, new perspectives for a public health issue: an integrative literature review. , 2019, Revista da Associacao Medica Brasileira.

[51]  Armelle M. Ngueleu,et al.  Validity of Instrumented Insoles for Step Counting, Posture and Activity Recognition: A Systematic Review , 2019, Sensors.