Channel Modeling of an Optical Wireless Body Sensor Network for Walk Monitoring of Elderly

Abstract

The growing aging of the world population is leading to an aggravation of diseases, which affect the autonomy of the elderly. Wireless body sensor networks (WBSN) are part of the solutions studied for several years to monitor and prevent loss of autonomy. The use of optical wireless communications (OWC) is seen as an alternative to radio frequencies, relevant when electromagnetic interference and data security considerations are important. One of the main challenges in this context is optical channel modeling for efficiently designing high-reliability systems. We propose here a suitable optical WBSN channel model for tracking the elderly during a walk. We discuss the specificities related to the model of the body, to movements, and to the walking speed by comparing elderly and young models, taking into account the walk temporal evolution using the sliding windowing technique. We point out that, when considering a young body model, performance is either overestimated or underestimated, depending on which windowing parameter is fixed. It is, therefore, important to consider the body model of the elderly in the design of the system. To illustrate this result, we then evaluate the minimal power according to the maximal bandwidth for a given quality of service.

Quality Indexes of the ECG Signal Transmitted Using Optical Wireless Link

“…Moreover, we used the switching combining method, which consists of processing data with a higher signal strength. It was verified in [13] that this configuration provides good communication coverage. Digital-to-analog conversion (DAC) was then applied to restitute the received ECG signal, the quality of which was evaluated by calculating high-layer metrics, i.e., SQIs.…”

“…of continuous wireless ECG monitoring [47]. Moreover, considering this data rate, we verified that channel delay dispersion and, therefore, inter-symbol interference, are negligible [13]. Then, the transmitter block allowed us to shape the signal according to the classic on-off keying (OOK) modulation by considering an average optical emitted power 𝑃 𝑡 .…”

“…The system to monitor the ECG signal of an elderly individual walking in a room is illustrated in Figure 1, based on the work presented in [13]. The environment is an empty room with dimensions of 6.6 × 6.7 × 3 m 3 .…”

“…To illustrate its impact on the ECG signal during walking, we have developed a simulation chain, which is presented in the following section. As explained in [13], the specific movements of the elderly person during walking were discretized from walking cycle recordings considering a speed of 0.5 m/s and a step of 20 cm in length, that is, a step duration T step = 0.4 s. The movement of the whole body was described using a random walk mobility model, illustrated as an example in Figure 2b.…”

“…In addition, it is a sustainable and inexpensive alternative to RF because it is possible to exploit existing lighting in visible light communication (VLC) as well as photovoltaic components to harvest energy and simultaneously decode optical signals [9]. As a result, OWC technology is now recognized as a solution for Internet of Things (IoT) applications [10], especially for medical data monitoring [11][12][13][14][15][16], ECG signal transmission [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31], and the connectivity of implantable medical devices [32].…”