Detecting and monitoring the symptoms of Parkinson's disease using smartphones: A pilot study

Arora, Siddharth; Venkataraman, Vinayak; Zhan, Andong; Donohue, S.; Biglan, Kevin; Dorsey, E. Ray; Little, Max A.

doi:10.1016/j.parkreldis.2015.02.026

Cited by 316 publications

(270 citation statements)

References 10 publications

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“…voice, gait, falls) and physical activity can potentially be monitored continuously and in the patient's own daily environment. It is hoped that in the future, such information might be used by clinicians to make better-informed management decisions [122]. However, much work remains needed in this field, for example to demonstrate the feasibility of wearable sensor technology (e.g.…”

Section: Treatment Sitementioning

confidence: 99%

Physical therapy and occupational therapy in Parkinson's disease

Radder

Sturkenboom

Nimwegen

et al. 2017

International Journal of Neuroscience

132

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Current medical management is only partially effective in controlling the symptoms of Parkinson's disease. As part of comprehensive multidisciplinary care, physical therapy and occupational therapy aim to support people with Parkinson's disease in dealing with the consequences of their disease in daily activities. In this narrative review, we address the limitations that people with Parkinson's disease may encounter despite optimal medical management, and we clarify both the unique and shared approaches that physical therapists and occupational therapists can apply in treating these limitations.

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Section: Treatment Sitementioning

confidence: 99%

Physical therapy and occupational therapy in Parkinson's disease

Radder

Sturkenboom

Nimwegen

et al. 2017

International Journal of Neuroscience

132

View full text Add to dashboard Cite

show abstract

“…Using wearable devices, various studies have shown that is possible to collect objective data regarding bradykinesia, tremor, dyskinesia, walking, sleep and speech that correlate to severity of disease, response to medication and track disease progression [87][88][89][90]. A recent study also showed that an intelligent closed-loop system integrating a wide range of wearable sensors, allowed physicians to remotely monitor the condition changes of the patients, adjust medication schedules, and individualize therapy in real-life conditions [91].…”

Section: Minimising Variability / Error In Assessing Endpointsmentioning

confidence: 99%

Challenges in detecting disease modification in Parkinson's disease clinical trials

Athauda

Foltynie

2016

Parkinsonism & Related Disorders

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Despite the wealth of encouraging data from numerous compounds that demonstrate "neuroprotection" in pre-clinical studies of Parkinson's disease, and despite numerous clinical trials, to date, no intervention has been demonstrated to able to modify the course of disease progression.While this "failure to translate" is likely due to numerous factors including our incomplete understanding of the pathogenic mechanisms underlying PD together with excessive reliance on data from the toxin-based animal models of PD, here we will discuss the "structural issues" pertaining to inadequate clinical trial design, selection of inappropriate endpoints and poor patient selection which are often not addressed following failed disease modification trials. Future directions to overcome these challenges such as reducing the heterogeneity of patient cohorts,

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“…Discrete Fourier Transform converts samples of a function (a signal that varies over time) into the list of coefficients of a finite combination of complex sinusoids (ordered frequency that has sample value). Fast Fourier transform converts time (signal) to frequency by decomposing an N point time domain signal into N signals [4] and Detrended Fluctuation Analysis is a method to determine self-affection of a signal [5]. Often Spectral Analysis (SA) is used in signal processing for PD's motor symptom assessment.…”

Section: Sensors Signals and Measuresmentioning

confidence: 99%

“…Digitizing tablet is used almost for all types of symptoms. Smartphone [5] and Microsoft Kinect (motion detector, and depth sensor) [15] are the latest devices in the market used for this. Smartphones (new generation of sensing devices) could expand rapidly with PD motor symptom assessments.…”

Section: Sensors Signals and Measuresmentioning

confidence: 99%

A Review of Parkinson’s Disease Cardinal and Dyskinetic Motor Symptoms Assessment Methods Using Sensor Systems

Aghanavesi

Westin

2016

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Abstract. This paper is reviewing objective assessments of Parkinson's disease (PD) motor symptoms, cardinal, and dyskinesia, using sensor systems. It surveys the manifestation of PD symptoms, sensors that were used for their detection, types of signals (measures) as well as their signal processing (data analysis) methods. A summary of this review's finding is represented in a table including devices (sensors), measures and methods that were used in each reviewed motor symptom assessment study. In the gathered studies among sensors, accelerometers and touch screen devices are the most widely used to detect PD symptoms and among symptoms, bradykinesia and tremor were found to be mostly evaluated. In general, machine learning methods are potentially promising for this. PD is a complex disease that requires continuous monitoring and multidimensional symptom analysis. Combining existing technologies to develop new sensor platforms may assist in assessing the overall symptom profile more accurately to develop useful tools towards supporting better treatment process.

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Detecting and monitoring the symptoms of Parkinson's disease using smartphones: A pilot study

Abstract: Study sponsorshipThis study received no external funding

Cited by 316 publications

References 10 publications

Physical therapy and occupational therapy in Parkinson's disease

Physical therapy and occupational therapy in Parkinson's disease

Challenges in detecting disease modification in Parkinson's disease clinical trials

A Review of Parkinson’s Disease Cardinal and Dyskinetic Motor Symptoms Assessment Methods Using Sensor Systems

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