zSense provides greater input expressivity for smart wearables through a shallow depth gesture recognition system using non-focused infrared sensors. To achieve this, we introduce a novel Non-linear Spatial Sampling (NSS) technique that significantly cuts down the number of required infrared sensors and emitters. These can be arranged in many different configurations; for example, number of sensor emitter units can be as minimal as one sensor and two emitters. We implemented different configurations of zSense on smart wearables such as smartwatches, smart-glasses and smart rings. These configurations naturally fit into the flat or curved surfaces of such devices, providing a wide scope of zSense enabled application scenarios. Our evaluations reported over 94.8% gesture recognition accuracy across all configurations.
- Anusha Withana, Roshan Peiris, Nipuna Samarasekara, and Suranga Nanayakkara. 2015. zSense: Enabling Shallow Depth Gesture Recognition for Greater Input Expressivity on Smart Wearables. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). ACM, New York, NY, USA, 3661-3670. [PDF]
Press and Awards
||zSense: Most Promising Technology Award at IHL Tech Pitching Event. May 2016. InnovFest 2016|
||zSense: First place in Singapore-MIT Alliance for Research and Technology (SMART) Bootcamp pitch competition. February 2016|
||Singapore designers create lights for the deaf and rings for the blind. November 2015. Hilary Whiteman, CNN|