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Portable Head-Mounted System for Mobile Forearm Tracking.

Matteo PolsinelliAlessandro Di MatteoDaniele LozziEnrico MatteiFilippo MignosiLorenzo NazziconeVincenzo StornelliGiuseppe Placidi
Published in: Sensors (Basel, Switzerland) (2024)
Computer vision (CV)-based systems using cameras and recognition algorithms offer touchless, cost-effective, precise, and versatile hand tracking. These systems allow unrestricted, fluid, and natural movements without the constraints of wearable devices, gaining popularity in human-system interaction, virtual reality, and medical procedures. However, traditional CV-based systems, relying on stationary cameras, are not compatible with mobile applications and demand substantial computing power. To address these limitations, we propose a portable hand-tracking system utilizing the Leap Motion Controller 2 (LMC) mounted on the head and controlled by a single-board computer (SBC) powered by a compact power bank. The proposed system enhances portability, enabling users to interact freely with their surroundings. We present the system's design and conduct experimental tests to evaluate its robustness under variable lighting conditions, power consumption, CPU usage, temperature, and frame rate. This portable hand-tracking solution, which has minimal weight and runs independently of external power, proves suitable for mobile applications in daily life.
Keyphrases
  • virtual reality
  • deep learning
  • low cost
  • physical activity
  • machine learning
  • endothelial cells
  • healthcare
  • optic nerve
  • heart rate
  • induced pluripotent stem cells