Comparison of the Parkinson’s KinetiGraph to off/on levodopa response testing: Single center experience

Guan, Ivan; Trabilsy, Maissa; Barkan, Samantha; Malhotra, Ashwin; Hou, Yu; Wang, Fei; Hellmers, Natalie; Sarva, Harini; Henchcliffe, Claire

doi:10.1016/j.clineuro.2021.106890

Cited by 7 publications

(3 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The PKG reliably and objectively evaluates motor symptoms, including bradykinesia, tremor, fluctuations, and dyskinesia, especially subtle changes in movement that may go unnoticed during clinical visits (Griffiths et al, 2012;Horne et al, 2015;Farzanehfar and Horne, 2017;Pahwa et al, 2020;Isaacson et al, 2022). These studies also highlight the value of PKG data in understanding disease progression and treatment response (Guan et al, 2021;Sundgren et al, 2021;Watts et al, 2021). Overall, PKG demonstrates great potential as a valuable tool for personalized precision medicine and improving prognosis in PwPD.…”

Section: Introductionmentioning

confidence: 91%

Identification and quantitative assessment of motor complications in Parkinson’s disease using the Parkinson’s KinetiGraph™

Qu,

Zhang,

Duo

et al. 2023

Front. Aging Neurosci.

View full text Add to dashboard Cite

IntroductionEffective management and therapies for the motor complications of Parkinson’s disease (PD) require appropriate clinical evaluation. The Parkinson’s KinetiGraph™ (PKG) is a wearable biosensor system that can record the motion characteristics of PD objectively and remotely.ObjectiveThe study aims to investigate the value of PKG in identifying and quantitatively assessing motor complications including motor fluctuations and dyskinesia in the Chinese PD population, as well as the correlation with the clinical scale assessments.MethodsEighty-four subjects with PD were recruited and continuously wore the PKG for 7 days. Reports with 7-day output data were provided by the manufacturer, including the fluctuation scores (FS) and dyskinesia scores (DKS). Specialists in movement disorders used the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale-IV (MDS-UPDRS IV), the wearing-off questionnaire 9 (WOQ-9), and the unified dyskinesia rating scale (UDysRS) for the clinical assessment of motor complications. Spearman correlation analyses were used to evaluate the correlation between the FS and DKS recorded by the PKG and the clinical scale assessment results. Receiver operating characteristic (ROC) curves were generated to analyze the sensitivity and specificity of the FS and DKS scores in the identification of PD motor complications.ResultsThe FS was significantly positively correlated with the MDS-UPDRS IV motor fluctuation (items 4.3–4.5) scores (r = 0.645, p < 0.001). ROC curve analysis showed a maximum FS cut-off value of 7.5 to identify motor fluctuation, with a sensitivity of 74.3% and specificity of 87.8%. The DKS was significantly positively correlated with the UDysRS total score (r = 0.629, p < 0.001) and the UDysRS III score (r = 0.634, p < 0.001). ROC curve analysis showed that the maximum DKS cut-off value for the diagnosis of dyskinesia was 0.7, with a sensitivity of 83.3% and a specificity of 83.3%.ConclusionThe PKG assessment of motor complications in the PD population analyzed in this study has a significant correlation with the clinical scale assessment, high sensitivity, and high specificity. Compared with clinical evaluations, PKG can objectively, quantitatively, and remotely identify and assess motor complications in PD, providing a good objective recording for managing motor complications.

show abstract

Section: Introductionmentioning

confidence: 91%

Identification and quantitative assessment of motor complications in Parkinson’s disease using the Parkinson’s KinetiGraph™

Qu,

Zhang,

Duo

et al. 2023

Front. Aging Neurosci.

View full text Add to dashboard Cite

show abstract

“…Objective assessments of the listed symptoms have been developed and tested for many years, but the validation of continuous measures throughout a day against a gold standard assessment is often limited ( Sica et al, 2021 ; Vanmechelen et al, 2022 ). Some IMU-based proprietary methods reported good correlations of passively generated symptom assessments and traditional gold standard assessments on larger temporal intervals ( Guan et al, 2021 ; Rodríguez-Martín et al, 2022 ). However, some passive assessments correlate better with gold standards on larger rather than shorter temporal intervals ( Joshi et al, 2019 ), where others only report their performance over larger periods of time ( Powers et al, 2021 ).…”

Section: Current Literaturementioning

confidence: 99%

Improving naturalistic neuroscience with patient engagement strategies

Feldmann,

Roudini,

Kühn

et al. 2024

Front. Hum. Neurosci.

View full text Add to dashboard Cite

IntroductionThe clinical implementation of chronic electrophysiology-driven adaptive deep brain stimulation (DBS) algorithms in movement disorders requires reliable representation of motor and non-motor symptoms in electrophysiological biomarkers, throughout normal life (naturalistic). To achieve this, there is the need for high-resolution and -quality chronic objective and subjective symptom monitoring in parallel to biomarker recordings. To realize these recordings, an active participation and engagement of the investigated patients is necessary. To date, there has been little research into patient engagement strategies for DBS patients or chronic electrophysiological recordings.Concepts and resultsWe here present our concept and the first results of a patient engagement strategy for a chronic DBS study. After discussing the current state of literature, we present objectives, methodology and consequences of the patient engagement regarding study design, data acquisition, and study infrastructure. Nine patients with Parkinson’s disease and their caregivers participated in the meeting, and their input led to changes to our study design. Especially, the patient input helped us designing study-set-up meetings and support structures.ConclusionWe believe that patient engagement increases compliance and study motivation through scientific empowerment of patients. While considering patient opinion on sensors or questionnaire questions may lead to more precise and reliable data acquisition, there was also a high demand for study support and engagement structures. Hence, we recommend the implementation of patient engagement in planning of chronic studies with complex designs, long recording durations or high demand for individual active study participation.

show abstract

“…This smartwatch is used to evaluate symptoms such as tremors, bradykinesia, and dyskinesia during activity in patients with Parkinson's disease. [28] Wearable Technologies for Athletes…”

Section: Parkinson's Kinetigraphmentioning

confidence: 99%

Evaluation of Wearable Technologies in Physiotherapy and Rehabilitation

Şahin

2024

BAU Health Innov

View full text Add to dashboard Cite

W earable technologies are defined as electronic devices which can be carried on clothes and accessories and provide psychological monitoring and biological feedback as well. Rings, bracelets, watches, jewelry such as lenses or spectacles, headbands, e-textile goods, and hearing aids are all types of wearable devices. [1] Wearable devices are considered one of the important applications of devices that can send and receive data over the internet, now called objects of the internet. Due to the widespread use of the Internet of Things, users' opportunities to take control of their health and make healthy life choices have increased thanks to devices that can be connected through the internet. [2] Wearable technologies can be used for different purposes, including health monitoring, management of chronic diseases, diagnosis and treatment of diseases, Wearable technologies are defined as electronic devices which can be carried on clothes and accessories and provide psychological monitoring and biological feedback as well. Rings, bracelets, watches, jewelry such as lenses or spectacles, headbands, e-textile goods, and hearing aids are all types of wearable devices. In this study, "wearable technologies," "physiotherapy," "physical activity," "sleep," and "smart textiles" keywords have been searched in PubMed, Google Scholar, Cochrane, and Scopus databases between 2001 and 2023. Wearable devices used in central nervous system diseases, athletes, sleep, physical activity, and weight control as well as smart textiles used in rehabilitation have been included in our study. Wearable technology makes it possible to expand the database of health-related information in addition to helping to monitor, improve, and maintain health. These technologies are commonly used in many diseases' diagnoses such as epilepsy and sleep disorders, in the follow-up of parameters related to physical activity and athlete's health, treatment, and rehabilitation processes of central nervous system diseases like Alzheimer's, and Parkinson's. In addition, smart textile products are used for sensory processing problems of individuals with autism spectrum disorder and figure out the risk of diabetic foot ulcers. By examining wearable technologies used for different purposes in physiotherapy and rehabilitation, this study contributes to the use of these technologies in new scientific studies.

show abstract

Comparison of the Parkinson’s KinetiGraph to off/on levodopa response testing: Single center experience

Cited by 7 publications

References 30 publications

Identification and quantitative assessment of motor complications in Parkinson’s disease using the Parkinson’s KinetiGraph™

Identification and quantitative assessment of motor complications in Parkinson’s disease using the Parkinson’s KinetiGraph™

Improving naturalistic neuroscience with patient engagement strategies

Evaluation of Wearable Technologies in Physiotherapy and Rehabilitation

Contact Info

Product

Resources

About