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Percorrer por autor "Kaizer, Raul"

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  • Data acquisition system for a wearable-based fall prevention
    Publication . Kaizer, Raul; Sestrem, Leonardo; Franco, Tiago; Gonçalves, João; Teixeira, João Paulo; Lima, José; Carvalho, José Augusto; Leitão, Paulo
    Reliable ways to treat and monitor patients remotely have been researched and proposed by numerous people. Many of these propositions are under the wearable category due to it usually not requiring deep knowledge to be handled and its durability. Among the many applicable ways, fall monitoring has gained importance as the world population ages and countries aim to increase the quality of life. For it to be possible, there are many ways such as analyzing muscle response, body position, or brain activities, but for most of them, the result ends up being expensive and or inaccurate. With this in mind, this paper brings the development of an acquisition system for electromyography, electrocardiography, body position and temperature. The acquired data is transmitted to the smartphone through Bluetooth Low Energy (BLE) and then sent to a secure cloud to be provided to the physician. In future works, artificial intelligence codes will analyze the data patterns to predict fall occurrences and establish functional electrical stimulation (FES) routines to prevent falls and or treat the patients according to their necessities.
    2023Comunicação em conferência Acesso aberto Ver mais
  • Data acquisition, conditioning and processing system for a wearable-based biostimulation
    Publication . Oliveira, Leonardo Sestrem de; Kaizer, Raul; Gonçalves, João; Leitão, Paulo; Teixeira, João Paulo; Lima, José; Franco, Tiago; Carvalho, José Augusto
    Data acquisition by electromyography, as well as the muscle stimulation, has become more accessible with the new developments in the wearable technology and medicine. In fact, for treatments, games or sports, it is possible to find examples of the use of muscle signals to analyse specific aspects related, e.g., to disease, injuries or movement impulses. However, these systems are usually expensive, does not integrate data acquisition with the muscle stimulation and does not exhibit an adaptive control behaviour that consider the pathology and the patient response. This paper presents a wearable system that integrates the signal acquisition and the electrostimulation using dry thin-film titanium-based electrodes. The acquired data is transmitted to a mobile application running on a smartphone by using Bluetooth Low Energy (BLE) technology, where it is analysed by employing artificial intelligence algorithms to provide customised treatments for each patient profile and type of pathology, and taking into consideration the feedback of the acquired electromyography signal. The acquired patient’s data is also stored in a secure cloud database to support the physician to analyse and follow-up the clinical results from the rehabilitation process.
    2022Comunicação em conferência Acesso aberto Ver mais