Virginie Felizardo

A review of thermal methods and technologies for diabetic foot assessment

Temperature analysis has been considered as a complementary method in medical evaluation and diagnosis. Several studies demonstrated that monitoring the temperature variations of the feet of diabetic patients can be helpful in the early identification of diabetic foot manifestations, and also in changing behaviors, which may contribute to reducing its incidence. In this review, several and most used techniques for assessing the temperature of the feet are presented, along with original published work on specific applications in diabetic foot complications. A review of solutions and equipment that operate according to the temperature assessment techniques is also presented. Finally, a comparison between the various technologies is presented, and the authors share their perspective on what will be the state of affairs in 5 years.

TICE.Healthy: A perspective on medical information integration

This paper describes a perspective on medical information integration as implemented by the Portuguese Program TICE.Healthy. The eight subprojects that integrate TICE.Healthy share a common database for medical data, and exchange data using standard formats. Because the subprojects deal with data of different nature, strategies were developed to allow the effective integration of this data. This paper describes the strategies adopted by the consortium, its discovered best practices and eventual pitfalls.

mHealth Sensors and Applications for Personal Aid

The evolution of medical equipment and health care involves the miniaturization and autonomy of devices that are responsible for medical monitoring, screening and even therapeutic actions.

Artificial Neural Learning Based on Big Data Process for eHealth Applications

The complexity of the clinical context requires systems with the capability to make decisions based on reduced sets of data. Moreover, the adoption of mobile and ubiquitous devices could provide personal health-related information. In line with this, eHealth application faces several challenges so as to provide accurate and reliable data to both healthcare professionals and patients. This chapter focuses on computational learning on the healthcare systems presenting different classification processes to obtain knowledge from data. Finally, a case study based on a radial basis function neural network aiming the estimation of ECG waveform is explained. The presented model revealed its adaptability and suitability to support clinical decision making. However, complementary studies should be addressed to enable the model to predict the upper and lower points related to upward and downward deflections.

Validation of a method for the estimation of energy expenditure during physical activity using a mobile device accelerometer

This work was supported by FCT project PEst-OE/EEI/L A0008/2013 (Este trabalho foi suportado pelo projecto FCT PEst-OE/EEI/LA0008/2013). The authors would also like to acknowledge the contribution of the COST Action IC1303 – AAPELE – Architectures, Algorithms and Protocols for Enhanced Living Environments.

Limitations of Energy Expenditure Calculation Based on a Mobile Phone Accelerometer

Sensors available in a mobile device, e.g., a smartphone, a smartwatch, or others, allow the capture of several signals, that may be used to the estimation of the energy expenditure. This paper describes the adaption of a previous research, using different signals and validated with a golden standard, consisting in the comparison between the units of the data acquired by a tri-axial accelerometer and an electromyography signal and the data collected by a mobile device accelerometer. The validation of the system showed that the energy expenditure may not be as correct as expected. The data related to this research is available in an open repository and the platform is available for testing. The creation of a validated method for the measurement of energy expenditure during physical activities capable for the implementation in a mobile application is an important issue to increase the confidence of the mobile applications in this market area.

Metabolic.Care: A Novel Solution Based on a Thermography for Detection of Diabetic Foot

The use of computer supported diagnosis for the early detection of illness-related complications is of utmost importance not only for the ill individual, but also for the society in general. This paper describes one approach to address the early detection of complications in diabetic feet, achieved by the use of a new device created using out-of-the box components, and complemented with a software ecosystem. This paper describes the solution and the ongoing research.

Electrocardiography, electromyography, and accelerometry signals collected with BITalino while swimming: Device assembly and preliminary results

The measurement of bio-signals is an important tool not only to assess the physical fitness, but also to prevent and/or to anticipate clinical episodes. In this paper a prototype to collect biosignals in water environments is described. This prototype collects three different signals such as accelerometry, electrocardiography, and electromyography, and was developed based on a modified off-the-shelf BITalino, to allow its use in water related bio-signal research. Several challenges are raised related with acquisition, transmission, and analysis of data, namely on defying environments such as swimming. The proposed model revealed it accuracy and suitability when applied on the swimming context.

Elderly mobility analysis during Timed Up and Go test using biosignals

With increasing life expectancy and a higher demand for quality of life it becomes more important to implement control tests for evaluate the mobility in the elderly people. The main objective of this work lies in the elderly mobility assessment through the acquisition of electromyography, and accelerometer signals while they perform the Timed Up and Go test. In this study participated 20 elderlies: 7 males and 13 females aged between 65 and 94 years. The study evaluated the biosignals electromyography in muscles rectus femoris, biceps femoris, rectus abdominis and lumbar iliocostalis. The triaxial accelerometer was placed on the head to measure the acceleration of the movement of the head while the elderly performs the Timed Up and Go test. With this work we confirm, as expected, a weak mobility among the participants, some being evaluated with very low disability and only a small part with reduced mobility. Finally, its essential to pay more efforts to create and improve forecasting strategies to prevent and/or identify mobility changes in the elderly.

Metabolic.Care: A hardware and software platform to monitor and assess diabetic foot condition

This paper describes Metabolic.Care, a sub-project that integrates hardware and software with the main goal of implementing a solution that generates warnings for the diagnosis on patients with diabetic foot. This paper also describes the adopted strategies and best practices found to solve the problems.