Towards remote evaluation of movement disorders via smartphones

Kostikis, Nikolaos; Hristu-Varsakelis, Dimitrios; Arnaoutoglou, Marianthi; Kotsavasiloglou, C.; Baloyiannis, S.

doi:10.1109/iembs.2011.6091296

Cited by 35 publications

(25 citation statements)

References 9 publications

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“…Other groups tried to develop similar iPhone applications to quantify tremor [29,30]. However, in contrast to the Itremor application, these applications were not yet validated clinically.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, our application included modalities for assessing not only postural tremor as in the work of LeMoyne et al [29 ]and Kostikis et al [30], but also action tremors. Moreover, Itremor has the advantage of being completely autonomous and the whole signal analysis is performed and displayed on the iPhone/iPod directly, without requiring any data transfer to an external computer by e-mail [29], or being Web-based and running on a distant computer [30]. As a result, Itremor is easily usable in the context of outpatient clinics or hospitalization by clinicians and nurses.…”

Section: Discussionmentioning

confidence: 99%

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Using the Accelerometers Integrated in Smartphones to Evaluate Essential Tremor

Senova¹,

Querlioz

Thiriez

et al. 2015

Stereotact Funct Neurosurg

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Background/Aims: Evaluation of tremor constitutes a crucial step from the diagnosis to the initial treatment and follow-up of patients with essential tremor. The severity of tremor can be evaluated using clinical rating scales, accelerometry, or electrophysiology. Clinical scores are subjectively given, may be affected by intra- and interevaluator variations due to different experience, delays between consultations, and subtle changes in tremor severity. Existing medical devices are not routinely used: they are expensive, time-consuming, not easily accessible. We aimed at showing that a smartphone application using the accelerometers embedded in smartphones is effective for quantifying the tremor of patients presenting with essential tremor. Methods: We developed a free iPhone/iPod application, Itremor, and evaluated different parameters on 8 patients receiving deep brain stimulation of the ventral intermediate nucleus of the thalamus: average and maximum accelerations, time above 1 g of acceleration, peak frequency, typical magnitude of tremor, for postural and action tremors, on and off stimulation. Results: We demonstrated good correlations between the parameters measured with Itremor and clinical score in all conditions. Itremor evaluation enabled higher discriminatory power and degree of reproducibility than clinical scores. Conclusion: Itremor can be used for routine objective evaluation of essential tremor, and may facilitate adjustment of the treatment.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Using the Accelerometers Integrated in Smartphones to Evaluate Essential Tremor

Senova¹,

Querlioz

Thiriez

et al. 2015

Stereotact Funct Neurosurg

View full text Add to dashboard Cite

show abstract

“…The iPhone application is envisioned to be operated by either the patient or through the assistance of a caregiver. Kostikis et al later in 2011 also applied a similar smartphone application for quantifying Parkinson's disease features [15].…”

Section: Wearable and Wireless Applications For Parkinson's Disease Qmentioning

confidence: 99%

Wearable and wireless accelerometer systems for monitoring Parkinson’s disease patients—A perspective review

LeMoyne¹

2013

APD

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Parkinson's disease is a growing medical concern as societies, such as the United States of America, become progressively aged. Therapy strategies exist for the amelioration of Parkinson's disease symptoms, and the quantification of attributes, such as hand tremor, can provide valuable feedback. Wearable and wireless accelerometer systems for monitoring Parkinson's disease patients have been progressively advanced over the course of the past half-decade. In particular, wireless accelerometer nodes and smartphones, such as the iPhone, hold promise for optimizing therapy strategy by providing convenient quantified feedback. This perspective review addresses the current advances in wearable and wireless accelerometer systems for monitoring Parkinson's disease patients and forecasts for the near future.

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“…Specialized equipment including electronic MIDI keyboards [2], accelerometers [5] and gyroscope sensors [5,6,7] have been used to capture kinematics of PD patients' performance of specific voluntary motor tasks. Data from patient-worn gyroscope and accelerometer sensors have also been used to effectively predict global dyskinesia severity during arm resting or extension [8], the severity of rest, postural and kinetic tremors [9], and speed, amplitude and rhythm components of UPDRS scores [4].…”

Section: Introductionmentioning

confidence: 99%

Smartphone application for classification of motor impairment severity in Parkinson's disease

Printy

Renken

Herrmann

et al. 2014

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Advanced hardware components embedded in modern smartphones have the potential to serve as widely available medical diagnostic devices, particularly when used in conjunction with custom software and tested algorithms. The goal of the present pilot study was to develop a smartphone application that could quantify the severity of Parkinson's disease (PD) motor symptoms, and in particular, bradykinesia. We developed an iPhone application that collected kinematic data from a small cohort of PD patients during guided movement tasks and extracted quantitative features using signal processing techniques. These features were used in a classification model trained to differentiate between overall motor impairment of greater and lesser severity using standard clinical scores provided by a trained neurologist. Using a support vector machine classifier, a classification accuracy of 0.945 was achieved under 6-fold cross validation, and several features were shown to be highly discriminatory between more severe and less severe motor impairment by area under the receiver operating characteristic curve (AUC > 0.85). Accurate classification for discriminating between more severe and less severe bradykinesia was not achieved with these methods. We discuss future directions of this work and suggest that this platform is a first step toward development of a smartphone application that has the potential to provide clinicians with a method for monitoring patients between clinical appointments.

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Towards remote evaluation of movement disorders via smartphones

Cited by 35 publications

References 9 publications

Using the Accelerometers Integrated in Smartphones to Evaluate Essential Tremor

Using the Accelerometers Integrated in Smartphones to Evaluate Essential Tremor

Wearable and wireless accelerometer systems for monitoring Parkinson’s disease patients—A perspective review

Smartphone application for classification of motor impairment severity in Parkinson's disease

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