Engin1000 / Das Boot Report. Project Summary Weight-bearing is a process of physical therapy pertaining to injuries below the waist that requires partial loading of the body weight on the recuperating leg, with the assistance of crutches or frames. Weight-bearing grades are typically determined by the therapist, and adjusted with the progress of healing. Without clinical equipment, patients are less able to rationally determine the amount of load placed on the injured leg. We are seeking to provide such accessibility to the patient in order to maximize the benefits of weight bearing. What we are proposing is a simple system that instantaneously determines the amount of pressure placed on the foot and provides a feedback that cautions the patient to gauge their motion. Our basic design involves a pressure-sensing sole (2) that calibrates the amount of pressure exerted on the foot and transmit the information via wireless to a micro-controller (3) to coordinate a form of signal back (1) to the user.
Project Design Pros. SENSEable Shoes | Computational Design Lab. SENSEable Shoes is a hands-free and eyes-free foot-computer interface that supports on-the-go interaction with surrounding environments. We recognize different low-level activities by measuring the user’s continuous weight distribution over the feet with twelve Force Sensing Resistor (FSR) sensors embedded in the insoles of shoes. Using the sensor data as inputs, a Support Vector Machine (SVM) classifier identifies up to eighteen mobile activities and a four-directional foot control gesture at approximately 98% accuracy.
By understanding user’s present activities and foot gestures, this system offers a nonintrusive and always-available input method. We present the design and implementation of our system and several proof-of-concept applications. A person’s weight is not allocated symmetrically over the plantar. We observed people’s common low-level activities in a mobile context and classified them as static or dynamic. We implement a SVM classifier with python’s Orange API.
Xsens : 3D Motion Tracking - Xsens. PrioVR VR Motion Tracking Suit: Interview with Head of R&D (video) Paul Yost, Head of R&D at YEI Technology After having checked out the first PrioVR prototype the other week, I had a chance to sit down with YEI Technology’s Head of R&D, Paul Yost, to learn more about the VR motion tracking system. Yost talks VR gloves, vests, and Post-Kickstarter plans. The PrioVR Kickstarter didn’t reach its goal, but the team is committed to making PrioVR a reality (11:51). Yost told me that the end of the Kickstarter is “…certainly not the end of the road for [PrioVR]….” This was YEI Technology’s first attempt at a crowd-funding project and that they learned much from the experience, Yost said. We also want to assure you that we’re not done. Yost told me (13:04) that development on the system is continuing regardless of the Kickstarter’s success and that “…the technology and the idea is too good for us to give up on….”
PrioVR Prototype Suit Yost also talked about using the PrioVR technology for an oft-requested ‘VR glove’ with full finger tracking (15:13). Www.yeitechnology.com/sites/default/files/Calculating Angles Between Two 3-Space Sensor Devices on a Human Body.pdf.