This is a scientific research project which purpose is to develop a virtual reality game to simulate a Para-Badminton match. This game will be tested with a professional Para- Badminton athlete who is a patient of LABRAL (Biomechanics and Rehabilitation of the Locomotor System) of Unicamp (State University of Campinas) and it aims to enhance his performance in Parabadminton and to reduce neuropathic pain. Neuropathic pain is described as a pain without any stimuli of nociceptors and is occurs in many patients with Spinal Cord Injury (SCI). This work is developed by LABCIBER (Biocybernetics and Rehabilitation Engineering) in the Department of Electrical Engineering - USP (University of São Paulo) at Sãao Carlos and it is supported by FAPESP (State of São Paulo Foundation for Research). This game uses Unity 3D game engine and Leap Motion hardware.

This paper presents the development of a humidity sensor based on bacterial nanocellulose membrane (BNC) produced from Komagataeibacter xylinus . BNC has a porous surface that absorbs water and therefore it changes the mechanical and electrical properties of the membrane. As the amount of water inside the membrane increases the capacitance of the membrane also increases. The capacitance of the BNC was measured in different values of temperature (from 30° to 100°) and relative humidity (from 30% to 100%). Chronoamperometry was used as a reproducibility test and the result was a linear and more precise variation for RH over 50% and a temperature of 30°. The measurements showed a combined sensitivity of -4.13nF/°C with relation to the temperature, and +492nF/(%RH) and +66.8nA/(%RH) with relation to the relative humidity.

The growth of digital communications has driven the development of numerous cryptographic methods for secure data transfer and storage. The SHA-256 algorithm is a cryptographic hash function widely used for validating data authenticity, identity, and integrity. The inherent SHA-256 computational overhead has motivated the search for more efficient hardware solutions, such as application-specific integrated circuits (ASICs). This work presents a custom ASIC hardware accelerator for the SHA-256 algorithm entirely created using open-source electronic design automation tools. The integrated circuit was synthesized using SkyWater SKY130 130 nm process technology through the OpenLANE automated workflow. The proposed final design is compatible with 32-bit microcontrollers, has a total area of 104,585 µm², and operates at a maximum clock frequency of 97.9 MHz. Several optimization configurations were tested and analyzed during the synthesis phase to enhance the performance of the final design.

This work presents the development and experimental validation of a low-cost, piezoelectret-based energy harvesting system integrated into a custom insole, as a promising alternative for future self-powered wearable electronics. The design utilizes eight thermoformed Teflon piezoelectrets, strategically positioned in high-impact regions (heel and forefoot), to convert footstep-induced mechanical motion into electrical energy. The sensors, fabricated using Fluorinated Ethylene Propylene (FEP) and Polytetrafluoroethylene (PTFE) layers via thermal pressing and aluminum sputtering, were connected in parallel to enhance signal consistency and robustness. A solenoid-actuated mechanical test rig was developed to simulate human gait under controlled conditions. The system consistently produced voltage pulses with peaks up to 13 V and durations exceeding ms, even under limited-force loading (10 kgf). Signal analysis confirmed repeatable waveform characteristics, and a Delon voltage multiplier enabled partial conversion into usable DC output. While not yet optimized for maximum efficiency, the proposed setup demonstrates the feasibility of using piezoelectrets for energy harvesting. Its simplicity, scalability, and low cost support its potential for future integration in applications such as fitness tracking, health monitoring, and GPS ultimately contributing to the development of autonomous, self-powered smart footwear systems. It is important to emphasize that the present study is a proof-of-concept validated exclusively under controlled laboratory conditions using a mechanical gait simulator. Future work will address real-time insole application tests with human participants.

Deep-Brain Stimulation (DBS) is a a highly effective and safe medical treatment that improves the lives of patients with a wide range of neurological and psychiatric deceases, and has been consolidated as a first-line tool in the treatment of these conditionsin the last two decades. Closed Loop Deep-Brain Stimulation (CLDBS) pushes this tool further by automatically adjusting the stimulation parameters to the brain response in real time. In this context, this paper presents a Low-Noise Amplifier (LNA) and a Neurostimulator circuits fabricated in the low-power/low-voltage 65 nm CMOS process from the TSMC, which were designed targeting implantable applications. To achieve the best trade-off between input-referred noise and power consuption, metaheuristic algorithms were employed to determine and optimizes the dimentions of the LNA devices during the design phase. The measurement results showed that the LNA had a gain of 40.6 dB, a 3 dB bandwidth spanning over three decades from 10 Hz to 8.6 kHz, and a power consumption of 6.19 uW. Simulations results indicated an input-referred noise of 4.86 uVrms for the LNA. The circuit of the Neurostimulator is a programmable Howland Current-Pump, whose measurements showed its ability to generate currents with arbitrary shapes ranging from between 325 uA to +318 uA. The simulations showed a quiescent power consumption of 0.13 W with a zero neurostimulation current. The LNA and the Neurostimulator circuits are supplied with 1.2 V voltage and occupy a microdevice area of 145 um x 311 um and 88 um x 89 um, respectively, making them suitable for implantation in applications involving Closed Loop Deep-Brain Stimulation.

Deep brain stimulation (DBS) is an effective and safe medical treatment that improves the lives of patients with a wide range of neurological and psychiatric diseases, and has been consolidated as a first-line tool in the last two decades. Closed-loop deep brain stimulation (CLDBS) pushes this tool further by automatically adjusting the stimulation parameters to the brain response in real time. The main contribution of this paper is a low-size/power-controlled, compact and complete CLDBS system with two simultaneous acquisition channels, two simultaneous neurostimulation channels and wireless communication. Each channel has a low-noise amplifier (LNA) buffer in differential configuration to eliminate the DC signal component of the input. Energy management is efficiently done by the control and communication unit. The battery supports almost 9 h with both the acquisition and stimulation circuits active. If only the stimulation circuit is used as an Open Loop DBS, the battery can hold sufficient voltage for 24 h of operation. The whole system is low-cost and portable and therefore it could be used as a wearable device.