{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T16:03:26Z","timestamp":1791302606235,"version":"4.1.0"},"reference-count":56,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,5,9]],"date-time":"2020-05-09T00:00:00Z","timestamp":1588982400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"A-WEAR European Union\u2019s Horizon 2020 (H2020) Marie Sklodowska-Curie Innovative Training Networks H2020-MSCA-ITN-Project","award":["813278"],"award-info":[{"award-number":["813278"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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\u2019s 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.<\/jats:p>","DOI":"10.3390\/s20092713","type":"journal-article","created":{"date-parts":[[2020,5,11]],"date-time":"2020-05-11T12:26:30Z","timestamp":1589199990000},"page":"2713","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":104,"title":["Wearable Solutions for Patients with Parkinson\u2019s Disease and Neurocognitive Disorder: A Systematic Review"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6728-2458","authenticated-orcid":false,"given":"Asma","family":"Channa","sequence":"first","affiliation":[{"name":"Computer Science Department, University POLITEHNICA of Bucharest, RO-060042 Bucharest, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nirvana","family":"Popescu","sequence":"additional","affiliation":[{"name":"Computer Science Department, University POLITEHNICA of Bucharest, RO-060042 Bucharest, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vlad","family":"Ciobanu","sequence":"additional","affiliation":[{"name":"Computer Science Department, University POLITEHNICA of Bucharest, RO-060042 Bucharest, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,9]]},"reference":[{"key":"ref_1","unstructured":"(2020, January 25). Alzheimer\u2019s Disease and Healthy Aging-Cognitive Impairment, Available online: https:\/\/www.cdc.gov\/aging\/pdf\/cognitive_impairment\/cogimp_poilicy_final.pdf."},{"key":"ref_2","unstructured":"Strydom, A., Fleisher, M.H., Deb, S., Ring, H., Esralew, L., Dodd, K., al Janab, T., Trollor, J., and Whitwham, S.L. (2020, May 09). Neurocognitive Disorders. Available online: https:\/\/www.ucl.ac.uk\/intellectual-developmental-disabilities-research\/sites\/intellectual-developmental-disabilities-research\/files\/DMID-2_Neurocognitive_disorders.pdf."},{"key":"ref_3","unstructured":"Durand, V.M., and Barlow, D.H. (2012). Essentials of Abnormal Psychology, Cengage Learning."},{"key":"ref_4","unstructured":"Naqvi, E. (2020, January 25). Parkinson\u2019s Disease Statistics. Available online: https:\/\/parkinsonsnewstoday.com\/parkinsons-disease-statistics\/?fbclid=IwAR3_8-8t1AzNT510ObUf6IdZ9PcyLHj_A2XFIUQAifBAbsSGfrbGh1lzDe0."},{"key":"ref_5","unstructured":"(2020, January 25). Parkinson\u2019s Disease. Available online: https:\/\/www.mayoclinic.org\/diseases-conditions\/parkinsons-disease\/symptoms-causes\/syc-20376055."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.ijge.2013.03.005","article-title":"Gait disorders in Parkinson\u2019s disease: Assessment and management","volume":"7","author":"Chen","year":"2013","journal-title":"Int. J. Gerontol."},{"key":"ref_7","first-page":"1683831","article-title":"Quantitative analysis of parkinsonian tremor in a clinical setting using inertial measurement units","volume":"2018","author":"Jonaitis","year":"2018","journal-title":"Park. Dis."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"375","DOI":"10.5334\/tohm.320","article-title":"Using portable transducers to measure tremor severity","volume":"6","author":"Elble","year":"2016","journal-title":"Tremor Other Hyperkinet. Mov."},{"key":"ref_9","unstructured":"(2020, January 25). How Wearable Tech Can Help People with Parkinson\u2019s Disease. Available online: https:\/\/www.apdaparkinson.org\/article\/wearable-technology-in-parkinsons\/."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1413","DOI":"10.1590\/1806-9282.65.11.1413","article-title":"Parkinson\u2019s disease and wearable devices, new perspectives for a public health issue: An integrative literature review","volume":"65","author":"Godoi","year":"2019","journal-title":"Rev. Assoc. M\u00e9d. Bras."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"602","DOI":"10.1016\/j.amjmed.2017.11.051","article-title":"Gait disorders","volume":"131","author":"Baker","year":"2018","journal-title":"Am. J. Med."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1016\/j.colegn.2017.11.005","article-title":"Mobility monitoring using smart technologies for Parkinson\u2019s disease in free-living environment","volume":"25","author":"Son","year":"2018","journal-title":"Collegian"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"555","DOI":"10.3389\/fnins.2017.00555","article-title":"How wearable sensors can support Parkinson\u2019s disease diagnosis and treatment: A systematic review","volume":"11","author":"Rovini","year":"2017","journal-title":"Front. Neurosci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/j.procs.2014.07.028","article-title":"Early Diagnosis of Parkinson\u2019s Disease Using a Smartphone","volume":"34","author":"Lan","year":"2014","journal-title":"Procedia Comput. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Margiotta, N., Avitabile, G., and Coviello, G. (2016, January 6\u20138). A wearable wireless system for gait analysis for early diagnosis of Alzheimer and Parkinson disease. Proceedings of the 2016 5th International Conference on Electronic Devices, Systems and Applications (ICEDSA), Ras Al Khaimah, UAE.","DOI":"10.1109\/ICEDSA.2016.7818553"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.compbiomed.2018.02.007","article-title":"Wrist sensor-based tremor severity quantification in Parkinson\u2019s disease using convolutional neural network","volume":"95","author":"Kim","year":"2018","journal-title":"Comput. Biol. Med."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.jns.2019.04.011","article-title":"Smartwatch for the analysis of rest tremor in patients with Parkinson\u2019s disease","volume":"401","author":"Velasco","year":"2019","journal-title":"J. Neurol. Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.jns.2018.02.001","article-title":"Quantification of whole-body bradykinesia in Parkinson\u2019s disease participants using multiple inertial sensors","volume":"387","author":"Memar","year":"2018","journal-title":"J. Neurol. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Tsipouras, M.G., Tzallas, A.T., Karvounis, E.C., Tsalikakis, D.G., Cancela, J., Pastorino, M., Waldmeyer, M.T.A., Konitsiotis, S., and Fotiadis, D.I. (2014, January 1\u20134). A wearable system for long-term ubiquitous monitoring of common motor symptoms in patients with Parkinson\u2019s disease. Proceedings of the IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), Valencia, Spain.","DOI":"10.1109\/BHI.2014.6864332"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.parkreldis.2015.11.004","article-title":"Feasibility and effects of home-based smartphone-delivered automated feedback training for gait in people with Parkinson\u2019s disease: A pilot randomized controlled trial","volume":"22","author":"Ginis","year":"2016","journal-title":"Park. Relat. Disord."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1109\/TBME.2012.2227317","article-title":"On-shoe wearable sensors for gait and turning assessment of patients with Parkinson\u2019s disease","volume":"60","author":"Mariani","year":"2012","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"6410","DOI":"10.1109\/JSEN.2019.2910105","article-title":"Monitoring Insole (MONI): A Low Power Solution Toward Daily Gait Monitoring and Analysis","volume":"19","author":"Hua","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.jns.2017.11.004","article-title":"Towards remote monitoring of Parkinson\u2019s disease tremor using wearable motion capture systems","volume":"384","author":"Delrobaei","year":"2018","journal-title":"J. Neurol. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"783","DOI":"10.1002\/mds.27709","article-title":"Clinical and methodological challenges for assessing freezing of gait: Future perspectives","volume":"34","author":"Mancini","year":"2019","journal-title":"Mov. Disord."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1843","DOI":"10.1109\/JBHI.2015.2465134","article-title":"Prediction of freezing of gait in Parkinson\u2019s from physiological wearables: An exploratory study","volume":"19","author":"Mazilu","year":"2015","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1016\/j.future.2017.04.036","article-title":"Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare","volume":"78","author":"Farahani","year":"2018","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"e12785","DOI":"10.2196\/12785","article-title":"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","volume":"21","author":"Piau","year":"2019","journal-title":"J. Med. Internet Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1873","DOI":"10.1109\/JBHI.2015.2461555","article-title":"An emerging era in the management of Parkinson\u2019s disease: Wearable technologies and the internet of things","volume":"19","author":"Pasluosta","year":"2015","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_29","first-page":"631","article-title":"Wearable sensors for advanced therapy referral in Parkinson\u2019s disease","volume":"6","author":"Heldman","year":"2016","journal-title":"J. Park. Dis."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1007\/s00702-015-1439-8","article-title":"Wearable sensor-based objective assessment of motor symptoms in Parkinson\u2019s disease","volume":"123","author":"Ossig","year":"2016","journal-title":"J. Neural Transm."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1293","DOI":"10.1002\/mds.26718","article-title":"Free-living monitoring of Parkinson\u2019s disease: Lessons from the field","volume":"31","author":"Godfrey","year":"2016","journal-title":"Mov. Disord."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"72","DOI":"10.3389\/fncom.2018.00072","article-title":"Optimizing clinical assessments in Parkinson\u2019s disease through the use of wearable sensors and data driven modeling","volume":"12","author":"Ramdhani","year":"2018","journal-title":"Front. Comput. Neurosci."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Sweeney, D., Quinlan, L.R., Browne, P., Richardson, M., Meskell, P., and \u00d3Laighin, G. (2019). A technological review of wearable cueing devices addressing freezing of gait in Parkinson\u2019s disease. Sensors, 19.","DOI":"10.3390\/s19061277"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Ngueleu, A.M., Blanchette, A.K., Maltais, D., Moffet, H., McFadyen, B.J., Bouyer, L., and Batcho, C.S. (2019). Validity of Instrumented Insoles for Step Counting, Posture and Activity Recognition: A Systematic Review. Sensors, 19.","DOI":"10.3390\/s19112438"},{"key":"ref_35","first-page":"176","article-title":"A wireless sensor insole for collecting gait data","volume":"200","author":"Rosevall","year":"2014","journal-title":"Stud. Heal. Technol. Inf."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1186\/s13063-016-1337-x","article-title":"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","volume":"17","author":"Hatton","year":"2016","journal-title":"Trials"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Han, Y., Cao, Y., Zhao, J., Yin, Y., Ye, L., Wang, X., and You, Z. (2016). A self-powered insole for human motion recognition. Sensors, 16.","DOI":"10.3390\/s16091502"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Qiu, F., Cole, M.H., Davids, K.W., Hennig, E.M., Silburn, P.A., Netscher, H., and Kerr, G.K. (2013). Effects of textured insoles on balance in people with Parkinson\u2019s disease. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0083309"},{"key":"ref_39","unstructured":"Mustufa, Y.A., Barton, J., O\u2019Flynn, B., Davies, R., McCullagh, P., and Zheng, H. (2015, January 9\u201312). Design of a smart insole for ambulatory assessment of gait. Proceedings of the 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN), Cambridge, MA, USA."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1111\/ane.12248","article-title":"Technical and clinical view on ambulatory assessment in Parkinson\u2019s disease","volume":"130","author":"Hobert","year":"2014","journal-title":"Acta Neurol. Scand."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1314","DOI":"10.1002\/mds.26693","article-title":"Machine learning for large-scale wearable sensor data in Parkinson\u2019s disease: Concepts, promises, pitfalls, and futures","volume":"31","author":"Kubota","year":"2016","journal-title":"Mov. Disord."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.medengphy.2017.12.006","article-title":"Automatic recognition of gait patterns in human motor disorders using machine learning: A review","volume":"53","author":"Figueiredo","year":"2018","journal-title":"Med. Eng. Phys."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.parkreldis.2019.03.022","article-title":"Evaluation of a sensor algorithm for motor state rating in Parkinson\u2019s disease","volume":"64","author":"Johansson","year":"2019","journal-title":"Park. Relat. Disord."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/j.rehab.2019.06.016","article-title":"Clinical effects of robot-assisted gait training and treadmill training for Parkinson\u2019s disease. A randomized controlled trial","volume":"62","author":"Capecci","year":"2019","journal-title":"Ann. Phys. Rehabil. Med."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.jphys.2019.08.003","article-title":"Home-based prescribed exercise improves balance-related activities in people with Parkinson\u2019s disease and has benefits similar to centre-based exercise: A systematic review","volume":"65","author":"Flynn","year":"2019","journal-title":"J. Physiother."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1159\/000481454","article-title":"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","volume":"64","author":"Gordt","year":"2018","journal-title":"Gerontology"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.parkreldis.2019.09.026","article-title":"Physiotherapy improves motor function in patients with the Parkinson variant of multiple system atrophy: A prospective trial","volume":"67","author":"Raccagni","year":"2019","journal-title":"Park. Relat. Disord."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/bs.irn.2019.08.004","article-title":"Wearable technological platform for multidomain diagnostic and exercise interventions in Parkinson\u2019s disease","volume":"147","author":"Hu","year":"2019","journal-title":"Int. Rev. Neurobiol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.jns.2019.02.031","article-title":"Mobility improves after high intensity aerobic exercise in individuals with Parkinson\u2019s disease","volume":"399","author":"Koop","year":"2019","journal-title":"J. Neurol. Sci."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"622","DOI":"10.1016\/j.apmr.2016.11.003","article-title":"Wearable sensor-based biofeedback training for balance and gait in Parkinson disease: A pilot randomized controlled trial","volume":"98","author":"Carpinella","year":"2017","journal-title":"Arch. Phys. Med. Rehabil."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1016\/j.jht.2017.08.001","article-title":"The effect of sensory-motor training on hand and upper extremity sensory and motor function in patients with idiopathic Parkinson disease","volume":"31","author":"Taghizadeh","year":"2018","journal-title":"J. Hand Ther."},{"key":"ref_52","first-page":"1650","article-title":"Design and development of a smart exercise bike for motor rehabilitation in individuals with Parkinson\u2019s disease","volume":"21","author":"Ridgel","year":"2015","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Heli, V.R., Rauhala, A., and Fagerstr\u00f6m, L. (2019). Person-centered home-based rehabilitation for persons with Parkinson\u2019s disease\u2013a scoping review. Int. J. Nurs. Stud., 103395.","DOI":"10.1016\/j.ijnurstu.2019.103395"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.cger.2019.09.008","article-title":"Multidisciplinary Care to Optimize Functional Mobility in Parkinson Disease","volume":"36","author":"Tosserams","year":"2019","journal-title":"Clin. Geriatr. Med."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1016\/j.jbmt.2017.07.006","article-title":"Timed up and go evaluation with wearable devices: Validation in Parkinson\u2019s disease","volume":"22","author":"Kleiner","year":"2018","journal-title":"J. Bodyw. Mov. Ther."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"32352","DOI":"10.1109\/ACCESS.2019.2901814","article-title":"Review of automated systems for upper limbs functional assessment in neurorehabilitation","volume":"7","author":"Baeza","year":"2019","journal-title":"IEEE Access"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/9\/2713\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:27:17Z","timestamp":1760174837000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/9\/2713"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,9]]},"references-count":56,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2020,5]]}},"alternative-id":["s20092713"],"URL":"https:\/\/doi.org\/10.3390\/s20092713","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,9]]}}}