An Application for Dementia Patient Monitoring with Sound Level Assessment Tool

A. Copiaco, C. Ritz, Stefano Fasciani, N. Abdulaziz
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Abstract

Dementia is an ailment heavily associated with cognitive decline and old age. Due to its progressive nature, several changes in sensory perceptions may be experienced by the individual. Thus, consistent monitoring of patients' assistance requirement, as well as the noise levels throughout their environment, can pose a challenge to caretakers. This is especially apparent for healthcare professionals working in nursing facilities. In this work, we propose an application with an intuitive interface that allows the acoustic monitoring of the patient without infringing their privacy. This is achieved through neural network-based sound scene classification and source location estimation models, which are trained with results of 98.80% and 99.68% F1-scores, respectively. Further, a sound level assessment tool is implemented, such that the time-average levels of the sound are compared to the recommended levels depending on the specific location and time of the day. Experimentation and implementation is carried out in MATLAB, while the interface was developed through the MATLAB App Designer, which can be exported into a mobile phone application as per required.
用声级评估工具监测痴呆患者的应用
痴呆症是一种与认知能力下降和衰老密切相关的疾病。由于其进行性,个体可能会经历一些感官知觉的变化。因此,持续监测患者的援助需求,以及整个环境中的噪音水平,可能对护理人员构成挑战。这对于在护理机构工作的医疗保健专业人员来说尤其明显。在这项工作中,我们提出了一个具有直观界面的应用程序,可以在不侵犯患者隐私的情况下对患者进行声学监测。这是通过基于神经网络的声音场景分类和源位置估计模型来实现的,这两个模型的训练结果分别为98.80%和99.68%的f1分数。此外,还实施了声级评估工具,以便根据一天中的具体位置和时间将声音的时间平均声级与建议声级进行比较。实验和实现是在MATLAB中进行的,界面是通过MATLAB App Designer开发的,可以根据需要导出为手机应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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