Internet of Things for Sensing: A Case Study in the Healthcare System

Abstract

Medical healthcare is one of the fascinating applications using Internet of Things (IoTs). The pervasive smart environment in IoTs has the potential to monitor various human activities by deploying smart devices. In our pilot study, we look at narcolepsy, a disorder in which individuals lose the ability to regulate their sleep-wake cycle. An imbalance in the brain chemical called orexin makes the sleep pattern irregular. This sleep disorder in patients suffering from narcolepsy results in them experience irrepressible sleep episodes while performing daily routine activities. This study presents a novel method for detecting sleep attacks or sleepiness due to immune system attacks and affecting daily activities measured using the S-band sensing technique. The S-Band sensing technique is channel sensing based on frequency spectrum sensing using the orthogonal frequency division multiplexing transmission at a 2 to 4 GHz frequency range leveraging amplitude and calibrated phase information of different frequencies obtained using wireless devices such as card, and omni-directional antenna. Each human behavior induces a unique channel information (CI) signature contained in amplitude and phase information. By linearly transforming raw phase measurements into calibrated phase information, we ascertain phase coherence. Classification and validation of various human activities such as walking, sitting on a chair, push-ups, and narcolepsy sleep episodes are done using support vector machine, K-nearest neighbor, and random forest algorithms. The measurement and evaluation were carried out several times with classification values of accuracy, precision, recall, specificity, Kappa, and F-measure of more than 90% that were achieved when delineating sleep attacks.

Chronic Obstructive Pulmonary Disease Warning in the Approximate Ward Environment

“…In a communication link, the channel properties must be known in advance, which could be analyzed with the help of wireless channel information (WCI). There exist multiple effects like scattering, fading, and multipath propagation [20], which affect the WCI of RF signal and which propagate between transmitter and receiver. The RF signal could be represented as follows,…”

Attack Graph Implementation and Visualization for Cyber Physical Systems

“…The pervasive smart environment in Internet of Things (IoTs) has the potential to monitor various human activities by using smart devices. For instance, [1] presented an approach for detecting sleep attacks due to immune system attacks, thus affecting daily activities measured using the S-band sensing method. The integration of wireless body area networks (WBANs) with recent cloud and sensor technologies offers significant improvement in the efficiency and the functionality of medical and health care systems [2].…”

Dataset

“…Human activity recognition is a field often tackled by this new idea of remote sensing. Research has shown that measuring physiological signals [5,7,9,10] and general activity recognition [1,5,6,11] can all be achieved through channel state information. The user-friendliness of remote systems is higher, as no wearables are required.…”