Clinical utility of a personalized and long-term monitoring device for Parkinson's disease in a real clinical practice setting: An expert opinion survey on STAT-ON™

Garcia, David; López-Ariztegui, N; Cubo, Esther; Aragón, Ana Vinagre; García-Ramos, R.; Borrué, Carmen; Fernández-Pajarín, Gustavo; Caballol, Núria; Cabo, Iria; Barrios-López, J.M.; Vara, Jorge Hernández; Rivera, María A. Ávila; Gasca-Salas, Carmen; Escalante, Sonia; Lara, P. Manrique de; Noguera, R. Pérez; Saúco, María Álvarez; Sierra, María; Monje, Mariana H.G.; Ferro, Álvaro Sánchez; Ponte, Sabela Novo; Alonso-Frech, Fernando; Macías‐García, Daniel; Legarda, I; Rojo, Ángela Sorli; Álvarez, Inés; Buongiorno, Maríateresa; Pástor, Pau; Ruiz, Pedro

doi:10.1016/j.nrl.2020.10.013

Cited by 9 publications

(14 citation statements)

References 26 publications

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“…The clinical evaluation in real clinical practice with STAT-ON TM has already started, although the first results have been achieved by having a great acceptance rate by different stakeholders: patients with PD, caregivers, neurologists, and healthcare professionals. The utility and acceptability in clinical practice are promising ( 54 ), and, although further research and validation should be carried out, results show the potential of an easy-to-use tool. The STAT-ON TM has achieved great results in user satisfaction and usability ( 105 ) and has been used in many cases ( 131 ), such as detection of motor fluctuations, dyskinesia, freezing of gait, therapy optimization, or second-line treatments' patients' selection.…”

Section: Discussionmentioning

confidence: 99%

“…Nonetheless, further studies are needed for early symptoms detection and to demonstrate the effectiveness of the device with different therapies. However, it seems that there is a consensus on using the device for the detection of candidates for second-line therapies ( 54 , 132 ). The Antonini et al consensus for the selection of patients for advanced therapies seems to align with the outcomes of STAT-ON TM , but additional findings are required to confirm this ( 135 ).…”

Section: Discussionmentioning

confidence: 99%

“…Another point and limitation is the understanding of the FoG algorithm. In ( 54 ), the FoG algorithm was considered one of the weaker algorithms. However, it has to be taken into account that this algorithm output is given every 1.6 s, while the ON-OFF is given every 30 min and the possibility to provide a false positive increases.…”

Section: Discussionmentioning

confidence: 99%

“…Finally, once a consistent clinical validation was achieved, Unobtrusive, Continuous, and Quantitative Assessment of Parkinson ' s disease: Hard Evidence for Optimal Disease Management with Information Technologies (PARK-IT2) project ( 104 ) was performed in order to redesign the existing prototype, embed the developed algorithms, industrialize and certify it as Medical Device Class IIa. The final device was considered clinically usable by a group of neurologists ( 54 ), and it is being validated in different pilots and clinical trials ( 105 , 106 ).…”

Section: Background On Stat-on Tm -Embedded Algori...mentioning

confidence: 99%

“…In 2020, Santos et al published the opinion of 27 clinical experts in movement disorders about STAT-ON TM after having tested the device in clinical practice ( 54 ). The general opinion of the neurologists was promising and with some important conclusions.…”

Section: Clinical Validation Of Stat-on Tmmentioning

confidence: 99%

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A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ONTM

et al. 2022

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In the past decade, the use of wearable medical devices has been a great breakthrough in clinical practice, trials, and research. In the Parkinson's disease field, clinical evaluation is time limited, and healthcare professionals need to rely on retrospective data collected through patients' self-filled diaries and administered questionnaires. As this often leads to inaccurate evaluations, a more objective system for symptom monitoring in a patient's daily life is claimed. In this regard, the use of wearable medical devices is crucial. This study aims at presenting a review on STAT-ONTM, a wearable medical device Class IIa, which provides objective information on the distribution and severity of PD motor symptoms in home environments. The sensor analyzes inertial signals, with a set of validated machine learning algorithms running in real time. The device was developed for 12 years, and this review aims at gathering all the results achieved within this time frame. First, a compendium of the complete journey of STAT-ONTM since 2009 is presented, encompassing different studies and developments in funded European and Spanish national projects. Subsequently, the methodology of database construction and machine learning algorithms design and development is described. Finally, clinical validation and external studies of STAT-ONTM are presented.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Background On Stat-on Tm -Embedded Algori...mentioning

confidence: 99%

Section: Clinical Validation Of Stat-on Tmmentioning

confidence: 99%

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A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ONTM

et al. 2022

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Virtual coach and telerehabilitation for Parkinson´s disease patients: vCare system

Del Pino,

de Echevarría,

Díez-Cirarda

et al. 2023

J Public Health (Berl.)

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Aim The vCare system is a virtual coach that involves physical and cognitive telerehabilitation and a daily life monitoring system. This pilot study aims to evaluate the vCare pilot test for Parkinson’s disease (PD) patients and to analyze the usability and the satisfaction level of patients and their quality of life (QoL). Subject and methods Twenty PD patients were randomized, 10 patients into the vCare group focused on personalized home telerehabilitation [motor and cognitive rehabilitation (4 days/week for 4 months)], while the control group (10 patients) continued the clinical standard at the clinic. A pre-post clinical evaluation and a cost-utility study were performed. Results Repeated measures ANOVA showed significant improvement in the PD vCare group compared to the control group (p<.05). Specifically, the PD vCare group showed significant improvement in cognition (p=.016), and QoL dimensions of mobility (p=.008), self-care (p=.008), daily activities (p=.010) and pain/discomfort (p=.004) at post-treatment. vCare PD patients showed high adherence to the vCare system (90.5-100%). Costs per patient in the control group were higher (€5,108.26) than in the vCare group (€2,243.07). Conclusion The PD vCare group significantly increase their QoL, cognition, motor symptoms, and daily life activities compared to the control group. Patients showed high adherence to the vCare coach, the care plan, rehabilitation, and devices. The vCare system seems to be an optimal and cost-effective tool for telerehabilitation in PD.

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Home-based monitoring of persons with advanced Parkinson’s disease using smartwatch-smartphone technology

Fay-Karmon,

Galor,

Heimler

et al. 2024

Sci Rep

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Movement deterioration is the hallmark of Parkinson’s disease (PD), characterized by levodopa-induced motor-fluctuations (i.e., symptoms’ variability related to the medication cycle) in advanced stages. However, motor symptoms are typically too sporadically and/or subjectively assessed, ultimately preventing the effective monitoring of their progression, and thus leading to suboptimal treatment/therapeutic choices. Smartwatches (SW) enable a quantitative-oriented approach to motor-symptoms evaluation, namely home-based monitoring (HBM) using an embedded inertial measurement unit. Studies validated such approach against in-clinic evaluations. In this work, we aimed at delineating personalized motor-fluctuations’ profiles, thus capturing individual differences. 21 advanced PD patients with motor fluctuations were monitored for 2 weeks using a SW and a smartphone-dedicated app (Intel Pharma Analytics Platform). The SW continuously collected passive data (tremor, dyskinesia, level of activity using dedicated algorithms) and active data, i.e., time-up-and-go, finger tapping, hand tremor and hand rotation carried out daily, once in OFF and once in ON levodopa periods. We observed overall high compliance with the protocol. Furthermore, we observed striking differences among the individual patterns of symptoms’ levodopa-related variations across the HBM, allowing to divide our participants among four data-driven, motor-fluctuations’ profiles. This highlights the potential of HBM using SW technology for revolutionizing clinical practices.

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Clinical utility of a personalized and long-term monitoring device for Parkinson's disease in a real clinical practice setting: An expert opinion survey on STAT-ON™

Cited by 9 publications

References 26 publications

A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ONTM

A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ONTM

Virtual coach and telerehabilitation for Parkinson´s disease patients: vCare system

Home-based monitoring of persons with advanced Parkinson’s disease using smartwatch-smartphone technology

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