# An IoT-Based Computational Framework for Healthcare Monitoring in Mobile Environments
## 2 Related Work
### Biomedical Sensing and Health Monitoring
[36] justifies the purpose of applying MCC in medical applications is to minimize the limitations of traditional medical treatment (e.g., small physical storage, security and privacy, and medical errors). Regarding to the specific case of sport monitoring, several studies have demonstrated the need to monitor the physical effort of athletes to provide knowledge of and tools for ensuring performance maintenance, training programme monitoring, prevention and reduction of athlete overtraining and injury [37; 38]. Increasingly, most coaches and training staff have adopted monitoring systems for doing their work more effectively by building custom train and rest plans and preserving the athletes' health [39; 40]. The most basic method for acquiring the information is by means of psychological questionnaires and surveys [41]. The Recovery-Stress Questionnaire for Athletes (RESTQ-Sport) was developed to assess the physical and mental impact of training stress and to facilitate the formulation of strategies for the enhancement of recovery [42]. Other self-report forms such as Profile of Mood States [43] and Daily Analysis of Life Demands [44] are also used. Other reported aspects are the quantity and quality of sleep. The work conducted by [PERSON] [45] demonstrated that sleep loss or deprivation can have significant effects on performance, motivation, perception of effort and cognition as well as numerous other biological functions. Thus, to keep an up-to-date register on sleep quantity and quality can be useful for early detection and intervention before significant performances and health decrements are observed. The new capabilities of sensors and wearables are able to collect human bio-signals during the training and competition stages establishing an athlete-technology interaction. For example, the research work performed by [PERSON] et al. [46] is focused on the sport of cycling where power output-measuring devices such as ergometers are used. Another representative example is the study carried out by [PERSON] and [PERSON] [47] focused on the fatigue and recovery aspects of rugby players. Different tests in the team sport context are developed such as the jump test (countermovement/squat jump), strength test, sprint performance, and isokinetic and isoinertial dynamometry as the athlete is doing exercise both during both competition and training time. These studies allow real-time monitoring of the effort rate made by muscles and the measurement of the neuromuscular function. The obtained data includes a number of parameters of physical activity such as average power, normalized power, speed, force, and acceleration. \begin{table}
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**Research** & **Biomedical Signals** & **Devices** \\ \hline Real-time streaming data in healthcare applications [34] & Generic Biomedical signals & Generic Biomedical sensors \\ \hline Recognition of activities and health monitoring [28] & Heart biomedical signals & Smartphones \& wearable devices \\ \hline Long-term monitoring of respiration and pulse [26] & Respiration and pulse & Non-contact sensors textile-integrated \\ \hline Diabetes monitoring [29] & Daily activity data & Smartphone \& smartwatch \\ \hline Active assistance [30] & Activity and environment data & Wearable sensors and smartphone \\ \hline Detect and prevent venous stasis [27] & Pulse and blood flow data & Multi-sensor plethysmography device \\ \hline Physiological data of elderly patients [33] & Oxygen saturation level, Heart Rate & Biomedical sensors \& smartphone \\ \hline ECG Smart Healthcare monitoring [31] & ECG signals & Wearable ECG sensors and Cloud for processing \\ \hline Mobile medical computing systems [32] & Medical signal and context information & Different sensors and actuators \\ \hline Applications in the pervasive environment [35] & Pulse rate, blood pressure, level of alcohol, etc. & Mobile healthcare \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Recent biomedical sensing research works.