A Kinematic Sensor and Algorithm to Detect Motor Fluctuations in Parkinson Disease: Validation Study Under Real Conditions of Use.

Alejandro Rodríguez-Molinero,David A Pérez-Martínez,Albert Samà,Andreu Català,Eva De Mingo,Carlos Pérez-López,Daniel Rodríguez-Martín,Alfons Moral,Ramiro Álvarez,Àngels Bayés,Jorge Hernández-Vara

doi:10.2196/rehab.8335

Abstract

BackgroundA new algorithm has been developed, which combines information on gait bradykinesia and dyskinesia provided by a single kinematic sensor located on the waist of Parkinson disease (PD) patients to detect motor fluctuations (On- and Off-periods).ObjectiveThe goal of this study was to analyze the accuracy of this algorithm under real conditions of use.MethodsThis validation study of a motor-fluctuation detection algorithm was conducted on a sample of 23 patients with advanced PD. Patients were asked to wear the kinematic sensor for 1 to 3 days at home, while simultaneously keeping a diary of their On- and Off-periods. During this testing, researchers were not present, and patients continued to carry on their usual daily activities in their natural environment. The algorithm’s outputs were compared with the patients’ records, which were used as the gold standard.ResultsThe algorithm produced 37% more results than the patients’ records (671 vs 489). The positive predictive value of the algorithm to detect Off-periods, as compared with the patients’ records, was 92% (95% CI 87.33%-97.3%) and the negative predictive value was 94% (95% CI 90.71%-97.1%); the overall classification accuracy was 92.20%.ConclusionsThe kinematic sensor and the algorithm for detection of motor-fluctuations validated in this study are an accurate and useful tool for monitoring PD patients with difficult-to-control motor fluctuations in the outpatient setting.

Highlights

Parkinson disease (PD) is the second most frequent neurodegenerative disease after Alzheimer, with an age-standardized annual incidence rate of 160 per 100,000 subjects aged 65 years or older [1]. Patients suffering from this disease present a motor disorder characterized by muscle stiffness and slow movement, sometimes accompanied by tremor and freezing of gait
Patients with advanced PD may present dyskinesia—involuntary and excessive movement of one or more body segments—which is related to excessive dopaminergic stimulation and, again, may be ameliorated by keeping plasmatic dopaminergic drugs at a stable level [4]
The goal of this study was to analyze the accuracy of the kinematic sensor and the algorithm under real conditions of use, in a group of PD patients with motor fluctuations

Summary

Introduction

Parkinson disease (PD) is the second most frequent neurodegenerative disease after Alzheimer, with an age-standardized annual incidence rate of 160 per 100,000 subjects aged 65 years or older [1] Patients suffering from this disease present a motor disorder characterized by muscle stiffness (rigidity) and slow movement (bradykinesia), sometimes accompanied by tremor and freezing of gait (patients feel their feet are stuck to the ground and cannot take a step). Patients were asked to wear the kinematic sensor for 1 to 3 days at home, while simultaneously keeping a diary of their On- and Off-periods During this testing, researchers were not present, and patients continued to carry on their usual daily activities in their natural environment. Conclusions: The kinematic sensor and the algorithm for detection of motor-fluctuations validated in this study are an accurate and useful tool for monitoring PD patients with difficult-to-control motor fluctuations in the outpatient setting

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Conclusion