SUMMARY

Parkinson's disease is the second most common neurodegenerative disease, with an estimated prevalence of 41/100,000 individuals affected aged between 40 and 49 years old and 1,900/100,000 aged 80 and over. Based on the essentiality of ascertaining which wearable devices have clinical literary evidence and with the purpose of analyzing the information revealed by such technologies, we conducted this scientific article of integrative review. It is an integrative review, whose main objective is to carry out a summary of the state of the art of wearable devices used in patients with Parkinson's disease. After the review, we retrieved 8 papers. Of the selected articles, only 3 were not systematic reviews; one was a series of cases and two prospective longitudinal studies. These technologies have a very rich field of application; however, research is still necessary to make such evaluations reliable and crucial to the well-being of these patients.

KEYWORDS:
Parkinson's Disease; Wearable Electronic Devices; Technology; Review; Public Health

RESUMO

A doença de Parkinson figura como a segunda doença neurodegenerativa mais comum. Sua prevalência é estimada de 41 por 100.000 pessoas entre 40 e 49 anos a 1.900 por 100.000 pessoas com 80 anos ou mais. Baseando-se na essencialidade de averiguar os dispositivos vestíveis que possuem evidências clínicas literárias e com o objetivo de analisar as informações reveladas por tais tecnologias, temos a construção deste artigo científico de revisão integrativa. Trata-se de uma revisão integrativa que tem como principal objetivo realizar um sumário do estado da arte de dispositivos vestíveis utilizados em pacientes com doença de Parkinson. Após realizada a revisão, obtiveram-se oito artigos. Pode-se observar que dos artigos selecionados, apenas três não eram revisões sistemáticas, sendo um deles uma série de casos e outros dois, estudos longitudinais prospectivos. A utilização dessas tecnologias possui um campo muito rico para atuar, contudo ainda são necessárias pesquisas para que tais avaliações sejam fidedignas e cruciais para o bem-estar desses pacientes.

PALAVRAS-CHAVE:
Doença de Parkinson; Dispositivos eletrônicos vestíveis; Tecnologia; Revisão; Saúde pública

INTRODUCTION

Parkinson's disease (PD) is a progressive neurodegenerative disease and characterized mainly by three typical motor symptoms: bradykinesia, muscle rigidity, and resting tremors¹1. Gelb DJ, Oliver E, Gilman S. Diagnostic criteria for Parkinson disease. Arch Neurol. 1999;56(1):33-9.. PD is the second most common neurodegenerative disease, with an estimated prevalence of 41 cases for every 100,000 individuals aged between 40 and 49 years and 1,900 cases for every 100,000 individuals aged 80 years or more. According to these calculations, respecting the differences of the populations studied, the diagnostic criteria and methods used, by 2030, there will be about 9 million people with PD²2. Pringsheim T, Jette N, Frolkis A, Steeves TD. The prevalence of Parkinson's disease: a systematic review and meta-analysis. Mov Disord. 2014;29(13):1583-90..

Given this scenario, the therapeutic management of patients has been one of the main challenges, mainly due to the lack of instruments to properly measure the therapeutic response to the treatment instituted and the motor signs displayed by the patient in their daily lives³3. Kassubek J. Diagnostic procedures during the course of Parkinson's disease. Basal Ganglia 2014;4:15-8..

In this context, the implementation of smart technologies for PD applications has increased in recent years. In particular, wearable sensors, which are a fundamental aid for early diagnosis, differential diagnosis, and in the objective quantification of symptoms in outpatients⁴4. Rovini E, Maremmani C, Cavallo F. How wearable sensors can support Parkinson's disease diagnosis and treatment: a systematic review. Front Neurosci. 2017;11:555.. The use of wearable technologies to measure daily data is an important tool that is currently viable to obtain frequent parameters for patient assessment, mainly because they demonstrate the reality of the individual's behavior outside of the clinical environment, which differs from the examination normally done in clinics.

Thus, there is an increasing demand for new and better technologies that are useful and clinically validated for the treatment or monitoring of diseases, PD included, even more so due its complexity and heterogeneity, which implies the need of clinical assessment and appropriate management, with constant analysis of symptoms, fluctuations, and observation of worsening of symptoms and progression of the disease³3. Kassubek J. Diagnostic procedures during the course of Parkinson's disease. Basal Ganglia 2014;4:15-8.^,55. Dickson JM, Grünewald RA. Somatic symptom progression in idiopathic Parkinson's disease. Parkinsonism Relat Disord. 2004;10(8):487-92.^–99. Del Din S, Godfrey A, Mazzà C, Lord S, Rochester L. Free-living monitoring of Parkinson's disease: Lessons from the field. Mov Disord. 2016;31(9):1293-313.. Currently, PD diagnosis is based on the assessment of motor and non-motor symptoms, as well as a neurological assessment. However, the diagnostic methods and approaches for monitoring disease progression disease remain below the ideal for the management of PD¹⁰10. Goetz CG, Tilley BC, Shaftman SR, Stebbins GT, Fahn S, Martinez-Martin P, et al; Movement Disorder Society UPDRS Revision Task Force. Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS): scale presentation and clinimetric testing results. Mov Disord. 2008;23(15):2129-70., with failures or gaps that can and should be improved. For example, although highly relevant for PD, the use of clinical scales such as the Unified Parkinson's DiseaseRating(UPDRS), is restrictive, since it depends on the patient's status at the moment of the evaluation (there may be, for example, an assessment bias in patients who have the ON/OFF phenomenon on motor symptoms), it is limited by subjectivity and the clinical experience of the professional assessing the patient. Wearable devices, therefore, overcame many of these limitations by objectively quantifying results that are clinically relevant so that the test variations are reduced by their use⁹9. Del Din S, Godfrey A, Mazzà C, Lord S, Rochester L. Free-living monitoring of Parkinson's disease: Lessons from the field. Mov Disord. 2016;31(9):1293-313.^,1111. Maetzler W, Rochester L. Body-worn sensors: the brave new world of clinical measurement? Mov Disord. 2015;30(9):1203-5.^,1212. Papapetropoulos S, Mitsi G, Espay AJ. Digital health revolution: is it time for affordable remote monitoring for Parkinson's disease? Front Neurol. 2015;6:34.. The measurement of motor symptoms by wearable devices is, in general, accurate and comparable to more established methods, with some of its aspects already tested and validated. The criteria evaluated refers to most of the motor symptoms (tremors, bradykinesia, dyskinesia) and have presented mostly moderate to high equivalence to standard clinical scales (for example, UPDRS, Modified Bradykinesia Rating Scale, among others)¹³13. Griffiths RI, Kotschet K, Arfon S, Xu ZM, Johnson W, Drago J, et al. Automated assessment of bradykinesia and dyskinesia in Parkinson's disease. J Parkinsons Dis. 2012;2(1):47-55..

Continuous long-term monitoring, therefore, has much more to offer in comparison to in-person clinical evaluations that may not reveal the true extent of symptoms¹⁴14. Espay AJ, Bonato P, Nahab FB, Maetzler W, Dean JM, Klucken J; Movement Disorders Society Task Force on Technology, et al. Technology in Parkinson's disease: challenges and opportunities. Mov Disord. 2016;31(9):1272-82.^,1515. Mellone S, Palmerini L, Cappello A, Chiari L. Hilbert-Huang-based tremor removal to assess postural properties from accelerometers. IEEE Trans Biomed Eng. 2011;58(6):1752-61.. Currently, such monitoring can be done from devices that utilize accelerometers, gyroscopes, magnetometers, and electromyography sensors, with possible uses such as the clinical observation of falls, tremors, bradykinesia, gait disorders, and mobility fluctuations¹⁵15. Mellone S, Palmerini L, Cappello A, Chiari L. Hilbert-Huang-based tremor removal to assess postural properties from accelerometers. IEEE Trans Biomed Eng. 2011;58(6):1752-61.. The most appropriate way to measure the motor performance of patients seems to be the use of wearable devices based on inertial sensors, which can acquire data with a high sampling rate¹³13. Griffiths RI, Kotschet K, Arfon S, Xu ZM, Johnson W, Drago J, et al. Automated assessment of bradykinesia and dyskinesia in Parkinson's disease. J Parkinsons Dis. 2012;2(1):47-55.^,1616. Palmerini L, Rocchi L, Mellone S, Valzania F, Chiari L. Feature selection for accelerometer-based posture analysis in Parkinson's disease. IEEE Trans Inf Technol Biomed. 2011;15(3):481-90.^–1818. Sejdić E, Lowry KA, Bellanca J, Perera S, Redfern MS, Brach JS. Extraction of stride events from gait accelerometry during treadmill walking. IEEE J. Transl Eng Health Med. 2016;4. pii: 2100111.. This has been developed for the assessment of several motor symptoms using a single or multiple systems.¹⁹19. Horne MK, McGregor S, Bergquist F. An objective fluctuation score for Parkinson's disease. PLoS One. 2015;10(4):e0124522.^,2121. Pastorino M, Cancela J, Arredondo MT, Pastor-Sanz L, Contardi S, Valzania F. Preliminary results of ON/OFF detection using an integrated system for Parkinson's disease monitoring. Conf Proc IEEE Eng Med Biol Soc. 2013;2013:941-4.^,1414. Espay AJ, Bonato P, Nahab FB, Maetzler W, Dean JM, Klucken J; Movement Disorders Society Task Force on Technology, et al. Technology in Parkinson's disease: challenges and opportunities. Mov Disord. 2016;31(9):1272-82.^,2222. Das S, Amoedo B, De la Torre F, Hodgins J. Detecting Parkinsons' symptoms in uncontrolled home environments: a multiple instance learning approach. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:3688-91.^–2424. Tzallas AT, Tsipouras MG, Rigas G, Tsalikakis DG, Karvounis EC, Chondrogiorgi M, et al. PERFORM: a system for monitoring, assessment and management of patients with Parkinson's disease. Sensors (Basel). 2014;14(11):21329-57.

The main purpose of domestic monitoring is to provide optimal management of PD. Therefore, wearable devices with inertial sensors may represent an optimal solution for healthcare applications both in the clinical and domestic environment¹²12. Papapetropoulos S, Mitsi G, Espay AJ. Digital health revolution: is it time for affordable remote monitoring for Parkinson's disease? Front Neurol. 2015;6:34.. Under this perspective, the importance of wearable devices in the diagnosis²⁵25. Baali H, Djelouat H, Amira A, Bensaali F. Empowering technology enabled care using iot and smart devices: a review. IEEE Sens. J. 2017;18(5):1790-809. and management of PD is clear⁹9. Del Din S, Godfrey A, Mazzà C, Lord S, Rochester L. Free-living monitoring of Parkinson's disease: Lessons from the field. Mov Disord. 2016;31(9):1293-313. since they can provide the physician with an understanding of the patient's scenario even in a simple evaluation⁹9. Del Din S, Godfrey A, Mazzà C, Lord S, Rochester L. Free-living monitoring of Parkinson's disease: Lessons from the field. Mov Disord. 2016;31(9):1293-313..

METHODS

This is an integrative review; according to Whitemore and Knalf²⁶26. Whittemore R, Knafl K. The integrative review: updated methodology. J Advanced Nursing. 2005;52(5):546-53., the “term integrative originated from the integration of opinions, concepts, or ideas from research used in the method,” which “highlights the potential to build science.” Furthermore, an integrative review is a subtype of a systematic literature review, which can be subdivided into meta-analysis, systematic review, qualitative review, or integrative review.

Thus, in line with what is presented by Botelho et al.²⁷27. Botelho LLR, Cunha CCA, Macedo M. O método da revisão integrativa nos estudos organizacionais. Gestão e Soc. 2011;5(11):121-36. and Redeker²⁸28. Redeker NS. Sleep in acute care settings: an integrative review. J Nurs Scholarsh. 2000;32(1):31-8., this integrative review has the main objective of summarizing the state of the art of wearable devices used in PD patients. In addition, we also analyzed in which types of symptoms (motor or not) such technologies are used and if the data presented demonstrated superior monitoring by wearable devices in comparison with outpatient follow-up, or if these are complementary approaches.

The review consisted in searching the IEEEXplore, Lilacs, PubMed, SciELO, Arxiv, and ScienceDirectdatabases by using the following groups of descriptors (in accordance with the MeSH terms, DeCS, and Bireme): (“Monitoring, Ambulatory” OR “Wearable Electronic Devices” OR “Biosensing Techniques”) AND “Parkinson Disease” AND “Motor Symptoms” AND (“Disease Progression” OR “Treatment Outcome”). These were reviewed following the PICO method for systematic reviews (Table 1).

The inclusion criteria were: original articles, of meta-analysis, systematic, or integrative review, published between 2011 and 2018, peer-reviewed, in English, with data related to the use of wearable devices in the therapeutic management of symptoms of PD patients. The exclusion criteria were papers on subjects unrelated to the research topic, gray bibliography, duplicate references, articles on books, written in languages other than English. Also, references that did not include any type of wearable sensor (device). On that basis, we initially retrieved 24 papers (Graph 1), of which, after reading of the titles and abstracts and applying the inclusion and exclusion criteria, seven remained for evaluation in their entirety. After that, we excluded one paper, which was a systematic review of all types of technologies in the bradykinesia evaluation of Parkinson's patients. However, it did not specifically evaluate the wearable devices. In addition, the references of the articles retrieved were evaluated manually in order to select other studies that had not been included during the database search. We added one more paper, a systematic review (Table 2), with a total of eight papers included in this review.

RESULTS

After the review, we found eight articles, which are listed in Table 2 with some of the conclusions by the authors of this paper after analyzing the data presented. Considering the data presented in Table 2, we noted a scarcity of articles whose objective is to demonstrate the longitudinal follow-up of PD patients through the use of wearable devices.

Out of the eight articles selected, only three were not systematic reviews; one was case series and two prospective longitudinal studies. Patel et al.²⁹29. Patel S, Chen BR, Mancinelli C, Paganoni S, Shih L, Welsh M, et al. Longitudinal monitoring of patients with Parkinson's disease via wearable sensor technology in the home setting. Conf Proc IEEE Eng Med Biol Soc. 2001;2011:1552-5. demonstrated in their study that by using a device called Mercurylive they could remotely assess two aspects of the UPDRS scale (Unified Parkinson's Disease Rating Scale), which is used mainly in the clinical environment, with the presence of the patient, to check, in particular, motor symptoms. The aspects evaluated in this study, as well as by the other two (Tzallas et al.²⁴24. Tzallas AT, Tsipouras MG, Rigas G, Tsalikakis DG, Karvounis EC, Chondrogiorgi M, et al. PERFORM: a system for monitoring, assessment and management of patients with Parkinson's disease. Sensors (Basel). 2014;14(11):21329-57.; Pastorino et al.²¹21. Pastorino M, Cancela J, Arredondo MT, Pastor-Sanz L, Contardi S, Valzania F. Preliminary results of ON/OFF detection using an integrated system for Parkinson's disease monitoring. Conf Proc IEEE Eng Med Biol Soc. 2013;2013:941-4.) are related to bradykinesia or daily motor fluctuations (ON/OFF phenomenon) (Figure 1). Considering that, in order to estimate the UPDRS scale, Patel et al.²⁹29. Patel S, Chen BR, Mancinelli C, Paganoni S, Shih L, Welsh M, et al. Longitudinal monitoring of patients with Parkinson's disease via wearable sensor technology in the home setting. Conf Proc IEEE Eng Med Biol Soc. 2001;2011:1552-5. showed that a longitudinal follow-up with evaluations in three days had an error of 0.4 points in relation to the clinical evaluation performed by a trained professional.

Tzallas et al.²⁴24. Tzallas AT, Tsipouras MG, Rigas G, Tsalikakis DG, Karvounis EC, Chondrogiorgi M, et al. PERFORM: a system for monitoring, assessment and management of patients with Parkinson's disease. Sensors (Basel). 2014;14(11):21329-57. used the Perform system (a prospective longitudinal study), which comprises three subsystems: a wearable device, a local-based unit, and a unit located at the hospital. With that, they found an accuracy of more than 80% to identify daily motor fluctuations (ON/OFF phenomenon), with an accuracy of 87.5% to identify resting tremors, 74.5% for bradykinesia, 79% for changes in gait, and 85.4% of accuracy for patients in the ON stage. The most significant error was of 0.79 in the identification of changes in gait.

Pastorino et al.²¹21. Pastorino M, Cancela J, Arredondo MT, Pastor-Sanz L, Contardi S, Valzania F. Preliminary results of ON/OFF detection using an integrated system for Parkinson's disease monitoring. Conf Proc IEEE Eng Med Biol Soc. 2013;2013:941-4., in a case series, assessed, for two consecutive days, the ON/OFF phenomenon by comparing the evaluation of wearable device with a self-assessment by the patient performed every 30 minutes, with three possible answers: OFF, ON with dyskinesia, and ON without with dyskinesia. We obtained an accuracy of 93.7% using the wearable device to identify motor fluctuations, compared with the self-assessment. They was also evaluated the comfort of using the technology, and 16% did not consider the device comfortable.

The other studies selected (Son et al.³⁰30. Son H, Park WS, Kim H. Mobility monitoring using smart technologies for Parkinson's disease in free-living environment. Collegian. 2018;25(5):549-60.; Ossig et al.³¹31. Ossig C, Antonini A, Buhmann C, Classen J, Csoti I, Falkenburger B, et al. Wearable sensor-based objective assessment of motor symptoms in Parkinson's disease. J Neural Transm (Vienna). 2016;123(1):57-64.; Del Din et al.⁹9. Del Din S, Godfrey A, Mazzà C, Lord S, Rochester L. Free-living monitoring of Parkinson's disease: Lessons from the field. Mov Disord. 2016;31(9):1293-313.; Godinho et al.³²32. Godinho C, Domingos J, Cunha G, Santos AT, Fernandes RM, Abreu D, et al. A systematic review of the characteristics and validity of monitoring technologies to assess Parkinson's disease. J Neuroeng Rehabil. 2016;13:24.) are systematic reviews that compiled studies, still incipient, about the use of wearable devices in PD patients.

DISCUSSION

Wearable devices mark the beginning of a new era in medical assistance, taking medicine to unimaginable new places and providing more precise and efficient diagnostics and treatments³³33. Chatterjee A, Gupta D. A study on the factors influencing the adoption: usage of wearable gadgets. 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT) 2017;1632-5.. In addition, the space occupied by this type of technology in modern medicine is evident. PD is a nosological entity that can be remotely evaluated by means of wearable devices⁹9. Del Din S, Godfrey A, Mazzà C, Lord S, Rochester L. Free-living monitoring of Parkinson's disease: Lessons from the field. Mov Disord. 2016;31(9):1293-313.^,2121. Pastorino M, Cancela J, Arredondo MT, Pastor-Sanz L, Contardi S, Valzania F. Preliminary results of ON/OFF detection using an integrated system for Parkinson's disease monitoring. Conf Proc IEEE Eng Med Biol Soc. 2013;2013:941-4.^,2424. Tzallas AT, Tsipouras MG, Rigas G, Tsalikakis DG, Karvounis EC, Chondrogiorgi M, et al. PERFORM: a system for monitoring, assessment and management of patients with Parkinson's disease. Sensors (Basel). 2014;14(11):21329-57.^,2929. Patel S, Chen BR, Mancinelli C, Paganoni S, Shih L, Welsh M, et al. Longitudinal monitoring of patients with Parkinson's disease via wearable sensor technology in the home setting. Conf Proc IEEE Eng Med Biol Soc. 2001;2011:1552-5.^–3232. Godinho C, Domingos J, Cunha G, Santos AT, Fernandes RM, Abreu D, et al. A systematic review of the characteristics and validity of monitoring technologies to assess Parkinson's disease. J Neuroeng Rehabil. 2016;13:24.^,3434. Hasan H, Athauda DS, Foltynie T, Noyce AJ. Technologies assessing limb bradykinesia in Parkinson's disease. J Parkinsons Dis. 2017;7(1):65-77., which can be defined as technologies that can be, literally, worn by the patient without interfering in activities of daily life or the progression of the disease. That is, they can be watches or sensors that send data to centrals (which may be located in the assistant physician clinic), for future evaluation of the evolution of the clinical condition³⁵35. Ometov A, Bezzateev SV, Kannisto J, Harju J, Andreev S, Koucheryavy Y. Facilitating the delegation of use for private devices in the era of the internet of wearable things. IEEE Internet Things J. 2017;4:843-54.^–4040. Hemapriya D, Viswanath P, Mithra VM, Nagalakshmi S, Umarani G. Wearable medical devices: design challenges and issues. 2017 Int. Conf. Innov. Green Energy Healthc. Technol. 1-6 (2017). doi:10.1109/IGEHT.2017.8094096
https://doi.org/10.1109/IGEHT.2017.80940... (Figure 2). There are several devices, still under development, which evaluate different aspects of PD patients to assess the progression of symptoms, motor or not, or even to estimate some clinical scales, such as the Unified Parkinson's Disease Rating Scale (UPDRS)²¹21. Pastorino M, Cancela J, Arredondo MT, Pastor-Sanz L, Contardi S, Valzania F. Preliminary results of ON/OFF detection using an integrated system for Parkinson's disease monitoring. Conf Proc IEEE Eng Med Biol Soc. 2013;2013:941-4.^,3030. Son H, Park WS, Kim H. Mobility monitoring using smart technologies for Parkinson's disease in free-living environment. Collegian. 2018;25(5):549-60.^,3434. Hasan H, Athauda DS, Foltynie T, Noyce AJ. Technologies assessing limb bradykinesia in Parkinson's disease. J Parkinsons Dis. 2017;7(1):65-77.. The Perform study aimed to describe the technological system for remote management and monitoring of PD patients regarding their: characteristics; features compared to other systems; assessment of motor symptoms in PD patients; analyses, and aid in the management of the disease.²⁴24. Tzallas AT, Tsipouras MG, Rigas G, Tsalikakis DG, Karvounis EC, Chondrogiorgi M, et al. PERFORM: a system for monitoring, assessment and management of patients with Parkinson's disease. Sensors (Basel). 2014;14(11):21329-57.. It is of great value for clinicians who follow-up these patients if these wearable devices can assist in monitoring patients, either in the initial approach, in diagnosis, prognosis, or even during treatment. In addition, it is important to check if there is a relevance of these evaluations by means of technologies comparing them to the evaluation performed by physicians. Hasan et al.³⁴34. Hasan H, Athauda DS, Foltynie T, Noyce AJ. Technologies assessing limb bradykinesia in Parkinson's disease. J Parkinsons Dis. 2017;7(1):65-77. conducted a study to estimate the UPDRS scale through evaluations conducted by patients and devices, which were then compared against each other and subsequently compared with clinical evaluations carried out by neurologists. However, they concluded that the use of such technologies was not superior to clinical assessments, despite having minimal errors in estimating the scale value³⁴34. Hasan H, Athauda DS, Foltynie T, Noyce AJ. Technologies assessing limb bradykinesia in Parkinson's disease. J Parkinsons Dis. 2017;7(1):65-77.. It is worth noting that the diagnosis of PD is eminently clinical⁴¹41. Beitz JM. Parkinson's disease: a review. Front Biosci (Schol Ed). 2014;6:65-74.. Moreover, in most cases, the monitoring and treatment are also performed at outpatient clinics, except for patients who require deep brain stimulation⁴²42. Okun MS. Deep-brain stimulation for Parkinson's disease. N Engl J Med. 2013;368(5):483-4.. Thus, it becomes clear that the use of technologies must demonstrate superior data to those already well known from clinical assessments, using once again the UPDRS scale as an example, which is summarized in clinical parameters by which the physician evaluates the progression of the disease and, most importantly, the motor symptoms, as well as the ON/OFF phenomenon, very common in patients with PD²¹21. Pastorino M, Cancela J, Arredondo MT, Pastor-Sanz L, Contardi S, Valzania F. Preliminary results of ON/OFF detection using an integrated system for Parkinson's disease monitoring. Conf Proc IEEE Eng Med Biol Soc. 2013;2013:941-4..

Studies have been developing wearable devices to evaluate and monitor patients with Parkinson's disease⁹9. Del Din S, Godfrey A, Mazzà C, Lord S, Rochester L. Free-living monitoring of Parkinson's disease: Lessons from the field. Mov Disord. 2016;31(9):1293-313.^,2121. Pastorino M, Cancela J, Arredondo MT, Pastor-Sanz L, Contardi S, Valzania F. Preliminary results of ON/OFF detection using an integrated system for Parkinson's disease monitoring. Conf Proc IEEE Eng Med Biol Soc. 2013;2013:941-4.^,2424. Tzallas AT, Tsipouras MG, Rigas G, Tsalikakis DG, Karvounis EC, Chondrogiorgi M, et al. PERFORM: a system for monitoring, assessment and management of patients with Parkinson's disease. Sensors (Basel). 2014;14(11):21329-57.^,2929. Patel S, Chen BR, Mancinelli C, Paganoni S, Shih L, Welsh M, et al. Longitudinal monitoring of patients with Parkinson's disease via wearable sensor technology in the home setting. Conf Proc IEEE Eng Med Biol Soc. 2001;2011:1552-5.^–3232. Godinho C, Domingos J, Cunha G, Santos AT, Fernandes RM, Abreu D, et al. A systematic review of the characteristics and validity of monitoring technologies to assess Parkinson's disease. J Neuroeng Rehabil. 2016;13:24.^,3434. Hasan H, Athauda DS, Foltynie T, Noyce AJ. Technologies assessing limb bradykinesia in Parkinson's disease. J Parkinsons Dis. 2017;7(1):65-77.. However, after analyzing the scope of each of them, it is noted that most focus on the assessment of motor symptoms, which are already very well known. In addition, not all motor symptoms are assessed, most devices assess, basically, bradykinesia and, consequently, the development or not of the ON/OFF phenomenon. In addition, those that aim to estimate some clinical scale do so by means of a few aspects, in comparison with the various tests performed in outpatient evaluations. It is undeniable that with the knowledge of artificial intelligence and technology in medicine, some medical approaches have become obsolete. In the case of patients with Parkinson's Disease, wearable devices are able to carry out a full evaluation of the patient at times when it is not possible for a physician to do the same. Consequently, they can detect oscillations in symptoms that do not occur during an outpatient evaluation performed by neurologists or other trained professionals³⁴34. Hasan H, Athauda DS, Foltynie T, Noyce AJ. Technologies assessing limb bradykinesia in Parkinson's disease. J Parkinsons Dis. 2017;7(1):65-77..

However, studies that assess the use of wearable devices are still few and bring previous results and a small sample of patients, so they are not representative of the entire population of PD patients. In addition, these technologies were not superior to clinical assessments, even though they cannot identify symptoms fluctuations throughout the day. Thus, further studies are necessary to assess other aspects of PD, such as non-motor symptoms that predict the prognosis of patients. Attention should also be paid to the wearability of these devices, i.e., their comfort, and the cost they will generate for health systems or individuals with the disease. Therefore, it is evident the need for controlled and prospective that confirm their effectiveness, since there are still some points to be improved, such as the duration of batteries, diagnosis differentiation between other motor disorders, and predictive values for PD or other conditions in pre-motor stage or very early diagnosis, which are still considered “enigmatic”¹⁶16. Palmerini L, Rocchi L, Mellone S, Valzania F, Chiari L. Feature selection for accelerometer-based posture analysis in Parkinson's disease. IEEE Trans Inf Technol Biomed. 2011;15(3):481-90.^,2121. Pastorino M, Cancela J, Arredondo MT, Pastor-Sanz L, Contardi S, Valzania F. Preliminary results of ON/OFF detection using an integrated system for Parkinson's disease monitoring. Conf Proc IEEE Eng Med Biol Soc. 2013;2013:941-4..

Considering the above, in agreement with Rocha et al.⁴³43. Rocha TAH, Fachini LA, Thumé E, Silva NC, Barbosa ACQ, Carmo M, et al. Saúde móvel: novas perspectivas para a oferta de serviços em saúde. Epidemiol Serv Saúde. 2016;25(1):159-70., wearable technologies used in PD must include the following features of any wearable device: monitoring, data transmission, analysis, diagnosis, and therapy, being able to minimize public health problems related to these patients.

The present study has some limitations; the technologies presented herein are restricted to those mentioned by scientific papers published in indexed journals. However, there may be other technologies that are in use and feature more reliable parameters than those clinically assessed. In addition, other factors should be taken into account, such as the populations in which technology was applied, the stage of the disease, as well as adherence to the pharmacological treatment established by the physician. These parameters are of paramount importance in patient assessment and in the results obtained with such technologies. We should also remember that some technologies may be in development, considering the results presented by these studies in order to improve the assessment and monitoring of patients with Parkinson's Disease.

CONCLUSION

The use of wearable devices is becoming very important for the development of medical care. Several companies are investing in technologies that are able to check motor fluctuations, such as in PD, or even identify the heart rate and possible acute arrhythmias. Thus, such technologies become allies of doctors, aiding in the diagnosis of certain diseases or in the monitoring to evaluate how the patient adapts to the therapy established.

PD is characterized as a public health issue, especially among the elderly population, and can benefit from these wearable devices, whether it is to evaluate daily fluctuations of motor symptoms, such as the ON/OFF phenomenon, or to predict the results of clinical scales, such as the UPDRS.

However, there are still several barriers to overcome because the results presented are still scarce and do not demonstrate superiority to the evaluations performed on an outpatient basis by the physician. In addition, it is of utmost importance that the various aspects that make up the clinical condition of patients are assessed, such as the motor symptoms (already evaluated, but not in its entirety) and the non-motor as well, which have not been evaluated by any wearable device. In short, these technologies can have very broad applications, yet more research is still needed for these assessments to be reliable and crucial to the well-being of patients.

REFERENCES

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