Non-Contact Thermal and Acoustic Sensors with Embedded Artificial Intelligence for Point-of-Care Diagnostics.

This work involves exploring non-invasive sensor technologies for data collection and preprocessing, specifically focusing on novel thermal calibration methods and assessing low-cost infrared radiation sensors for facial temperature analysis. Additionally, it investigates innovative approaches to analyzing acoustic signals for quantifying coughing episodes. The research integrates diverse data capture technologies to analyze them collectively, considering their temporal evolution and physical attributes, aiming to extract statistically significant relationships among various variables for valuable insights. The study delineates two distinct aspects: cough detection employing a microphone and a neural network, and thermal sensors employing a calibration curve to refine their output values, reducing errors within a specified temperature range. Regarding control units, the initial implementation with an ESP32 transitioned to a Raspberry Pi model 3B+ due to neural network integration issues. A comprehensive testing is conducted for both fever and cough detection, ensuring robustness and accuracy in each scenario. The subsequent work involves practical experimentation and interoperability tests, validating the proof of concept for each system component. Furthermore, this work assesses the technical specifications of the prototype developed in the preceding tasks. Real-time testing is performed for each symptom to evaluate the system's effectiveness. This research contributes to the advancement of non-invasive sensor technologies, with implications for healthcare applications such as remote health monitoring and early disease detection.

Recombinant Limb Assay as in Vivo Organoid Model.

Organ formation initiates once cells become committed to one of the three embryonic germ layers. In the early stages of embryogenesis, different gene transcription networks regulate cell fate after each germ layer is established, thereby directing the formation of complex tissues and functional organs. These events can be modeled in vitro by creating organoids from induced pluripotent, embryonic, or adult stem cells to study organ formation. Under these conditions, the induced cells are guided down the developmental pathways as in embryonic development, resulting in an organ of a smaller size that possesses the essential functions of the organ of interest. Although organoids are widely studied, the formation of skeletal elements in an organoid model has not yet been possible. Therefore, we suggest that the formation of skeletal elements using the recombinant limb (RL) assay system can serve as an in vivo organoid model. RLs are formed from undissociated or dissociated-reaggregated undifferentiated mesodermal cells introduced into an ectodermal cover obtained from an early limb bud. Next, this filled ectoderm is grafted into the back of a donor chick embryo. Under these conditions, the cells can receive the nascent embryonic signals and develop complex skeletal elements. We propose that the formation of skeletal elements induced through the RL system may occur from stem cells or other types of progenitors, thus enabling the study of morphogenetic properties in vivo from these cells for the first time.

Early diagnosis of frailty: Technological and non-intrusive devices for clinical detection.

This work analyses different concepts for frailty diagnosis based on affordable standard technology such as smartphones or wearable devices. The goal is to provide ideas that go beyond classical diagnostic tools such as magnetic resonance imaging or tomography, thus changing the paradigm; enabling the detection of frailty without expensive facilities, in an ecological way for both patients and medical staff and even with continuous monitoring. Fried's five-point phenotype model of frailty along with a model based on trials and several classical physical tests were used for device classification. This work provides a starting point for future researchers who will have to try to bridge the gap separating elderly people from technology and medical tests in order to provide feasible, accurate and affordable tools for frailty monitoring for a wide range of users.