Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Bruna Alves has a total of 4 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Gait Cycle Duration Analysis in Lower Limb Amputees Using an IoT-Based Photonic Wearable Sensor: A Preliminary Proof-of-Concept Study

    by Bruna Alves, Alessandro Fantoni, José Pedro Matos, João Costa, Manuela Vieira

    This study represents a preliminary proof of concept intended to demonstrate the feasibility of using a single-point LiDAR sensor for wearable gait analysis. The study presents a low-cost wearable sensor system that integrates a single-point LiDAR module and IoT connectivity to assess Gait Cycle Duration (GCD) and gait symmetry in real time. The device is positioned on the medial side of the calf to detect the contralateral limb crossing—used as a proxy for mid-stance—enabling the computation of GCD for both limbs and the derivation of the Symmetry Ratio and Symmetry Index. This was conducted under simulated walking at three cadences (slow, normal and fast). GCD estimated by the sensor was compared against the visual annotation with Kinovea®, showing reasonable agreement, with most cycle-wise relative differences below approximately 13% and both methods capturing similar symmetry trends. The wearable system operated reliably across different speeds, with an estimated materials cost of under 100 € and wireless data streaming to a cloud dashboard for real-time visualization. Although the validation is preliminary and limited to a single healthy participant and a video-based reference, the results support the feasibility of a photonic, IoT-based approach for portable and objective gait assessment, motivating future studies with larger and clinical cohorts and gold-standard references to quantify accuracy, repeatability and clinical utility.


  • Open Access

    Gait Cycle Duration Analysis in Lower Limb Amputees Using an IoT-Based Photonic Wearable Sensor

    by Bruna Alves, Alessandro Fantoni, José Pedro Matos, João Costa, Manuela Vieira

    The sensor effectively detected mid-stance events and adapted to variations in gait cadence. Comparison with Kinovea® showed a reasonable agreement, with most relative differences under 13%. Both methods identified similar gait symmetry trends. The results confirm the feasibility of the proposed system for real-time gait assessment across different walking speeds. Although preliminary, this validation supports the potential of the device as a low-cost, portable, and objective tool for functional evaluation in prosthetic rehabilitation. Further studies are needed to expand validation with clinical populations and laboratory-grade reference systems.