# Portable Sensor System for Registration, Processing and Mathematical Analysis of PPG Signals
## 1 Introduction
### Research Background
In their study, the authors of [29] describe the created multi-site measurement system for the analysis of eight PPG signals and one ECG signal simultaneously registered. The investigated signals are recorded online and the data processed offline while using the Matlab development environment. The analyzes were performed on signals received from 16 volunteers. The system can be used for medical diagnostics. Pulse Rate Variability analysis and Heart Rate Variability analysis applications for cardiological data can be grouped into two main groups: desktop applications and web-based applications. Desktop applications must be installed or developed for a particular operating system and they must have strict hardware requirements to ensure the proper functioning of the application. This hardware dependency might be a disadvantage for some users. The most popular desktop applications for Heart Rate Variability analysis are: Kubios HRV software [30], CODESNA [31], SinusCor [32], gHRV [33], and others. Traditional web-based applications [34; 35; 36; 37] offer a single database. The centralized architecture of these applications allows for you to store all of your data in one place. The installation, setup, and maintenance of the software is web based. All of the changes and modifications to the system are made on the server of the system without having to be reflected in different jobs. This makes their maintenance efficient, fast, and inexpensive. In modern medicine, there is an acute problem that is associated with organizing the process of continuous monitoring of indicators that determine the physical condition of the human body (photoplethysmograms, electrocardiograms, blood pressure, pulse, breathing, temperature) of patients being treated in hospitals and clinics with minimal involvement of nursing staff and observed patients when they are at work or home. Body Sensor Networks (BSNs) have been created to solve this problem, which are a continuation of Wireless Sensor Networks. BSNs are fast-paced in healthcare, fitness, rehabilitation, emotion recognition, and many other applications of the Internet of Things, thus enabling 24/7 monitoring of at-risk patients. BSNs collect sensitive data from various sensors located on the human body and use computational technologies for signal processing and machine learning to retrieve information. Combining data from multiple heterogeneous, sensory sources becomes a basic but non-trivial task for BSN. In a publication [38], the authors discuss the motives and advantages of multisensor data synthesis, focusing on identifying the physical activity of the subjects studied, identifying parameters that influence the choice of data design at different levels (data, function, and decision). A major issue in the development of BSN for blood pressure monitoring, which is essentially related to the development of portable sensor devices, being characterized by small size, optimal placement, and low power consumption, is discussed in [39]. BSNs are progressing towards multi-technology integration and intelligence. With the advent of cloud technologies, BSNs are evolving toward the long-term monitoring of several vital human health indicators, long-term storage, and engagement with application services. The future of BSN is fundamentally promising, which will profoundly change human-machine relationships and improve people's quality of life [40]. On the basis of the conducted research for the existing photoplethysmographic systems, the following summary can be made: photoplethysmographic systems perform the following activities: registration of PPG signals, processing, mathematical analysis of the defined PP interval series, and evaluation of the obtained results. These systems record PPG signals of different duration: minutes, hours, 24 h, and perform assessments of various factors (cardiovascular disease, diseases of the autonomic-nervous system, physical and emotional stress, bad habits, etc.) that affect the human body.