# Artificial Intelligence, Sensors and Vital Health Signs: A Review
## 2 Related Works
Among the reviewed works on cardiovascular diseases, only a few studies provided details on the patient's gender; the notable differences between men and women make this an important factor affecting the validity of the results. Concerning the population samples in the analyzed studies, 56% conducted their studies with up to twenty samples of the data, and only 20% of the works conducted their analysis with fifty-one samples. Therefore, the less amount of data used is a shortcoming, and it was recommended that further studies should use larger data. Similarly, in [11], the results of the performance of traditional threshold-based alarm frameworks that are used to analyze physiological parameters were studied. The study data were obtained from adult participants who were admitted to the clinical ward after elective major surgery in the Netherlands (Amsterdam University Medical Centre, Amsterdam, Netherlands) between 2018 and 2019. Data were obtained from a total of sixty participants, of which twenty-one were exempted from the analysis due to the unavailability of wireless vital signs devices. The results obtained in this study revealed that the-state-of-the-art classical threshold-based alarm system recognized anomalies in vital signs before or after treatment in the majority of the observed adverse events in ward patients and recommended the development of several methods for adaptive alarm thresholds may enhance the recognition of clinical deterioration at early stages in ward patients. An IoT-based ambulatory vital signs data transfer system was proposed by [12], and a prototype model of the proposed system was developed using an IoT-based medical sensor board and a Linux server imitating the conventional hospital server. This proposed system was designed to transmit the vital health signs of various patients to a remote location server for possible emergency handling by physicians. The system also displays the data of multiple patients on a screen for visual observation and analysis. The recorded vital signs data of the patients are also sent to a smart IoT device, where the results are presented in a graphical form for easy analysis. For this proposed system, it was assumed that mobile connectivity would be available during any emergency, but because a disaster could be of different degrees, and cellular activity can be affected during certain disasters, this system may be ineffective. Another interesting review [1] aimed at finding the optimum approach for implementing an IoT health monitoring platform. In their work, eighteen different articles published between 2016 and 2018 were reviewed, and it was recommended that the use of health monitoring systems that use wearable sensors and smart-watches, as studied in the papers reviewed, was a low-cost solution to health monitoring in general, and the tendency of doctors to monitor every symptom and vital signs at the hospital, most of which are not done in real-time due to a lack of capable medical personnel, can greatly affect the general outcome of the clinical processes. It was also reported that the photoplethysmogram (PPG) sensor was the best sensor; it has a low error rate, is small in size, and is widely adopted in physiological parameter measurement. In addition, the PPG sensor detects early vital signs and symptoms of health problems. A contactless radar-based sensor for vital signs monitoring was presented in [13]. The proposed system can be deployed to monitor the vital signs (heartbeat and respiration) of multiple patients in a real-world setting. It does not need a wearable device for its operation. In addition, two algorithms were developed for target tracking and rejection of random body movements. The system can also keep track of individuals during movement. The experiments for the proposed system were carried out in two environments: a laboratory and an office area. The equipment used was a radar module, a digital signal processor/field-programmable gate array (DSP/FPGA) board, an analogue-to-digital converter (ADC), and a laptop.