# Internet of Things for Sensing: A Case Study in the Healthcare System
## 1 Introduction  
The Internet of Things (IoT) is a concept reflecting a connected set of anyone, anything, anytime, any service, and any network [1]. The Internet of Thing is a discussion and trend that has been going on in the tech industry for a while. There are two big things to note about IoTs; first, the average individual does not leverage it greatly. Second, IoTs takes analog ideas or devices, such as sensors, actuators, home appliances etc., and connects them through inter-networking [2].  
IoTs provides appropriate solutions for a wide range of applications such as smart cities, traffic congestion, waste management, structural health, security, emergency services, logistics, retails, industrial control, and health care [1].  
Medical healthcare is one of the fascinating applications for IoTs. The pervasive smart environment leveraging IoTs has a potential to monitor various human's activities by the deployment of smart devices. Recently, in the medical healthcare domain, the research focus has moved toward human activity recognition. Daily routine activities have a prospect to be monitored and supported by IoTs. Patient's activity detection is a vital issue for caregivers with adequate information about the subject can be documented in healthcare systems. Activity recognition enables nurses or caretakers to provide timely assistance. For instance, in a pervasive environment, a caregiver can monitor activity using devices such as a computer or mobile phone to provide instant care for subject in risky situations [3]. For these reasons, we seek to incorporate small wireless devices used in S-band sensing technique to monitor the sleep attacks of patients suffering from narcolepsy disease (ND).  
Narcolepsy is a neurological disorder in which individuals lose the ability to regulate their sleep-wake cycle. The normal cycle between sleeping and being awake is blurred, leading to sleeping excessively during the day [4]. It is an impairment with symptoms such as acute drowsiness and falling asleep without any prior warning. Loss of orexin neurons in the brain is attributed to the disruption of transitions between sleep-wake states [5]. People suffering from narcolepsy disorder have fewer excitatory neurons, and each neuron carries less of the neuropeptides orexin A and orexin B [6]. These orexins increase the activity of wake-promoting regions of the brain, thereby tipping the scales in favor of wakefulness and preventing inappropriate transitions into a sleeping state. ND primarily damages the neurons delivering orexin, and therefore less orexin is sent out and sleep-related symptoms start to intrude into wakefulness. ND can be triggered by activities such as walking, exercise, etc. or sudden, strong emotions like anger or excitement [7]. Narcolepsy sleep episodes typically last up to few minutes.  
In a nutshell, patients suffering from narcolepsy fall asleep involuntary while doing daily activities. Continuous monitoring of ND patients, for targeted treatment--particularly the elderly--is of the utmost importance to avoid the risk of injury or to shed light on its triggers [5]. Thus, to monitor the daily routine activities of ND patients, we use the S-Band sensing technique leveraging wireless devices such as card, omni-directional antenna, etc. Each human activity generates a particular wireless channel information imprint in terms of variances of amplitude and phase information that is used to detect various human activities for sleep attack experiences by ND patients. The amplitude and phase information obtained are classified using support vector machine (SVM), K-nearest neighbor (KNN), and random forest (RF) for identifying sleep attacks.