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. 2019 Feb 12;19(3):737.
doi: 10.3390/s19030737.

A Non-Invasive Medical Device for Parkinson's Patients with Episodes of Freezing of Gait

Catalina Punin  1 , Boris Barzallo  2 , Roger Clotet  3 , Alexander Bermeo  4 , Marco Bravo  5 , Juan Pablo Bermeo  6 , Carlos Llumiguano  7
Affiliations

A Non-Invasive Medical Device for Parkinson's Patients with Episodes of Freezing of Gait

Catalina Punin et al. Sensors (Basel). .

Abstract

A critical symptom of Parkinson's disease (PD) is the occurrence of Freezing of Gait (FOG), an episodic disorder that causes frequent falls and consequential injuries in PD patients. There are various auditory, visual, tactile, and other types of stimulation interventions that can be used to induce PD patients to escape FOG episodes. In this article, we describe a low cost wearable system for non-invasive gait monitoring and external delivery of superficial vibratory stimulation to the lower extremities triggered by FOG episodes. The intended purpose is to reduce the duration of the FOG episode, thus allowing prompt resumption of gait to prevent major injuries. The system, based on an Android mobile application, uses a tri-axial accelerometer device for gait data acquisition. Gathered data is processed via a discrete wavelet transform-based algorithm that precisely detects FOG episodes in real time. Detection activates external vibratory stimulation of the legs to reduce FOG time. The integration of detection and stimulation in one low cost device is the chief novel contribution of this work. We present analyses of sensitivity, specificity and effectiveness of the proposed system to validate its usefulness.

Keywords: Parkinson’s disease; clinical assessment; discrete wavelet transform; freezing of gait; neurodegenerative disorders; sensors; vibratory stimulus.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
How Parkinson’s disease originates [25].
Figure 2
Figure 2
Decomposition wavelet in five levels: tree topology.
Figure 3
Figure 3
Acceleration in patients 5 and 6, performed in the lower extremities.
Figure 4
Figure 4
(a) Printed Circuit Board with components; (b) Encapsulated device in ergonomic support; (c) Device placed in patient.
Figure 5
Figure 5
Graphical interface of application “FOG Detection” (a) home screen; (b) results screen/stimulus OFF; (c) results screen/stimulus ON.
Figure 6
Figure 6
Signals of patients with FOG.
Figure 7
Figure 7
Signals of patients without FOG.
Figure 8
Figure 8
Distribution of total energy in the subbands of the wavelet coefficients.
Figure 9
Figure 9
Percentage distribution of energy in the subbands of the coefficients.
See this image and copyright information in PMC

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