Validation of Freezing-of-Gait Monitoring Using Smartphone.

Background: Freezing of gait (FOG) is a commonly observed motor symptom for patients with Parkinson's disease (PD). The symptoms of FOG include reduced step lengths or motor blocks, even with an evident intention of walking. FOG should be monitored carefully because it not only lowers the patient's quality of life, but also significantly increases the risk of injury.

Wrist sensor-based tremor severity quantification in Parkinson's disease using convolutional neural network.

Tremor is a commonly observed symptom in patients of Parkinson's disease (PD), and accurate measurement of tremor severity is essential in prescribing appropriate treatment to relieve its symptoms. We propose a tremor assessment system based on the use of a convolutional neural network (CNN) to differentiate the severity of symptoms as measured in data collected from a wearable device. Tremor signals were recorded from 92 PD patients using a custom-developed device (SNUMAP) equipped with an accelerometer and gyroscope mounted on a wrist module.

Tremor frequency characteristics in Parkinson's disease under resting-state and stress-state conditions.

Tremor characteristics-amplitude and frequency components-are primary quantitative clinical factors for diagnosis and monitoring of tremors. Few studies have investigated how different patient's conditions affect tremor frequency characteristics in Parkinson's disease (PD). Here, we analyzed tremor characteristics under resting-state and stress-state conditions.

Clinicians' Tendencies to Under-Rate Parkinsonian Tremors in the Less Affected Hand.

The standard assessment method for tremor severity in Parkinson's disease is visual observation by neurologists using clinical rating scales. This is, therefore, a subjective rating that is dependent on clinical expertise. The objective of this study was to report clinicians' tendencies to under-rate Parkinsonian tremors in the less affected hand.

Adaptive windowing for gait phase discrimination in Parkinsonian gait using 3-axis acceleration signals.

In order to robustly analyze the gait of Parkinson's disease (PD) patients, a new gait phase discrimination method was developed for analyzing the three-axis accelerations of the ankle during walking. The magnitude of acceleration was compared with the lowpass-filtered signal of itself and pseudo foot-flat phases were determined. Four narrow windows were made sequentially and adaptively from the pseudo foot-flat phases.

Classification of Parkinson gait and normal gait using Spatial-Temporal Image of Plantar pressure.

The purpose of this paper is the classification of Spatial-Temporal Image of Plantar pressure (STIP) among normal step and the patients step of Parkinson disease. For this, we created a new image data, STIP, that have information of the change of plantar pressure during heel to toe motion (i.e.