Leader: Daniele Fiaschi (UNIFI); Other collaborator(s): UNIFI
This task aims to extend the knowledge of the metabolic behavior of the human body using Internet of Things (IoT) solutions for the monitoring of the subject (low-cost sensors, infrared & Thermo camera imaging) and by the development of novel thermodynamic models of the human body, describing heat transfer and energy/exergy balances. The general objective of this study is to assess whether the thermo-hygrometric balance and the other biometrics parameters could be monitored quantitatively and/or modified by ad hoc physical activity, which has already shown to be able to restore specific functional and clinical parameters in patients, possibly prolonging life expectancy by improving their conditions. The data measured during the monitoring tests, carried out on real subjects, can be used to calibrate the parameters of the above-mentioned thermodynamic models and to validate their results. This new approach should be integrated with the well-established biomedical monitoring - adding quantitative values to the phenomenological effects, such as thermal dispersion.
The final goal is to gather quantitative data and to improve the predictability of the patient’s response ensuring the appropriate type and level of exercise, calibrated as a function of ageing, and maximizing the benefits at a physical and psychological level.
During the concerned period (November 2023-March 2024): The foundational framework of the human body’s thermodynamic model has been entirely redefined. The existing model excels in precision regarding data acquisition, particularly due to its focus on the experimental setup. Rigorous adherence to international standards has been a key aspect of the modelling process to ensure the model’s validity before transitioning to the testing phase. Presently, the model is undergoing integration into thermodynamic software such as PTC® Mathcad® Prime and the F-Chart Software Engineering Equation Solver (EES), scrutinizing for potential errors related to thermodynamics and, more broadly, assessing measurements and instrumentation or identifying avenues for further enhancement.
The thermodynamic model, originally constructed using Mathcad and EES, has been ported to the Python programming language to ensure accessibility via license-free platforms such as GitHub. One motivation for sharing the package on GitHub is to facilitate version control, alongside continuous integration and continuous development (CI/CD) practices. Additionally, this dissemination provides greater flexibility for incorporating data from external sources to support further testing and refinement. The model has been structured as a Python package employing object-oriented programming (OOP) principles, facilitating installation within a Python environment. This package comprises diverse modules, each housing methods tailored to accomplish specific tasks.
On the instrumentation front, a meticulous shortlisting of sensors and instruments has taken place, with outreach to original equipment manufacturers (OEMs) or distributors for quotation requests. The ongoing process involves the collection of three quotations for each product. Quotations for major instruments, including the Infrared Thermal Imaging Camera and Body Core Temperature measurements, have already been obtained and MEPA code is issued. The delivery of the product is expected in the coming month.
Main policy, industrial and scientific implications:
Practice implications:
Please see the next reporting period.
The activities of the Task were mainly devoted on two directions: (i) improvements of the thermodynamic framework, and (ii) definition of the Standard Operating Procedure (SOP). Regarding the first activity, the thermodynamic model underwent initial development and thorough error testing using PTC® Mathcad® and F-Charts® EES. Upon achieving satisfactory performance, it is transitioned to Python for enhanced accessibility and shared on GitHub®. With respect to the previous version, the current Python package, Human-Body-Heat-Transfer, includes modules assessing metabolism and its interaction with physical activity and aging, encompassing:
To examine the thermogenic responses across age groups at varying exercise intensities, a Standard Operating Procedure (SOP) has been identified. In details, the following protocol is established:
A sample of 10 participants (5 males, 5 females) will be drawn from specific age groups (20–29 years, 30–39 years, 40–49 years, 50–59 years, 60–69 years, 70–79 years), with exclusions for individuals with walking impairments or serious medical conditions. Considering the instrumentation, the study will utilize: (i) COSMED K5 (cardiopulmonary analyser), (ii) FLIR® A700 SC Kit (thermal imaging), (iii) CORE Sensor (core temperature), and (iv) Wearable bands. This asset will allow the measurement of VO2 and metabolism during exercise and recovery, so that the following experimental output can be computed:
Main policy, industrial and scientific implications:
This represented a fundamental period for the research, with the beginning of the experimental activities in the gymnasium and the data analysis in relationship to the development of the advanced multi parts body model, which has reached its validation phase. The study protocol, equipment, and subject sampling have been established. A preliminary version of the research project, along with informed consent forms regarding data processing, has been submitted to the ethics committee. Sixty subjects will be analyzed, equally divided between males and females across various age decades groups. Preliminary tests have successfully demonstrated the compatibility of thermographic and metabolic data. The testing environment has been established within a dedicated room at Healthfarm gym, where the accuracy and feasibility of the procedures have been verified.
Intermediate results:
These insights provide a comprehensive understanding of how the body responds and adapts to various stages of exercise, highlighting the dynamic interplay between respiratory parameters, metabolic rate, heat loss mechanisms, HR, VO2, RQ, and body temperature. The experimental behavior are generally in agreement with the advanced multi parts body model, paving the way for the subsequent assessment of thermodynamic relationships of metabolism with physical exercise level at different ages.
Scientific publications