Long-Short Term Neural Network Analysis of Center of Pressure of Gait

Long-Short Term Neural Network Analysis of Center of Pressure of Gait

Arshia Khan (University of Minnesota, Duluth, USA) and Janna Madden (University of Minnesota, Duluth, USA)
DOI: 10.4018/IJEACH.2020010102

Abstract

Detection of vascular dementia in early stages of cognitive impairment is difficult to do in a clinical setting since the earliest changes are often discrete and physiological in nature. One major aspect of this is gait patterns. This project utilizes force-sensing platforms, motion capture, and EMG sensors to unobtrusively collect biometric data from an individual's walking gait patterns. The data parameters gathered were center of pressure, gait phase and end of unloading/toe-ff events. By quantifying and analyzing machine learning algorithms, specifically deep learning time-series based models, onset patterns of vascular dementia are explored with an overarching goal of creating a system that will assist in understanding and diagnosing cases of vascular dementia. The proposed system provides a tool for which gait can be analyzed and compared over a long period of time and opens opportunity to increased personalization in health monitoring and disease diagnosis and provides an avenue to increase patient-centricity of medical care. Since gait is one of the early predictors of vascular dementia, we developed a long short-term neural network to predict the gait variations from which we can predict the onset of vascular dementia.
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Background

Vascular Dementia

Progression of Vascular Dementia generally represents a stepwise decline, appearing suddenly after an episode and aggravated from the following episodes, but without the continuous decline common to Alzheimer’s Disease. Vascular Dementia transitions from preclinical to Vascular Cognitive Impairment to Vascular Dementia, of which can be sub-classified as mild, moderate or severe. To understand diagnosis, the symptoms and expected progression at each of these stages must be considered. The initial stage is often described as “silent” as the brain begins to change without measurable obvious symptoms. Because of this, much that is known about the preclinical stage of Vascular Dementia is based on retrospective evaluations of records of diagnosed cases. One such study found that patients had memory complaints 12 years prior to diagnosis and had experienced declines in activities of daily living 5 to 7 years previous to diagnosis (Verlinden et. al, 2016). While Vascular Dementia patients had memory complaints 12 years prior to diagnosis, cognitively, there is comparatively less deterioration in the preclinical stage as compared to other forms of Dementia. Patients’ with incident vascular dementia deteriorate earlier and faster in daily functioning, especially the more physical activities of daily living such as activities, arising, dressing and grooming, eating, hygiene, grip, reach, and walking, as compared to other forms of Dementia that experience the first changes in cognitive activities such as finance management, phoning, medication use, housekeeping, and meal preparation (Verlinden et al., 2016, Sperling et al., 2011). The progression from preclinical to Vascular Cognitive Impairment is a very slight transition. The Vascular Cognitive Impairment stage is loosely defined as cases where one or more cognitive domains becomes significantly affected (Serge et al., 2006, Stephan et al., 2009). At this stage in the disease, symptoms are becoming clinically detectable and while noticeable in daily living, not generally too limiting in this respect. Identifying the onset of other cognitive impairment and the relationship between the Vascular episode and other cognitive impairments is one of the great challenges facing research in this area.1

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