Recently, tiny smart devices have become increasingly popular in our lives because of neat features and stylish appearance. However, their tiny sizes bring about new challenges to human-device interaction applications. Although some novel methods have been put forward, they possess different defects and are not able to deal with this problem thoroughly. As a result, we propose acoustic-based sensing methods for different kinds of HCI applications such as texts entry, gesture recognition, and etc. For more details, please refer to the following publications.
Papers: [PerCom'19][ICDCS'19][TMC'21][THMS'22]
Demos: [AirTouch][EchoType]

User authentication on smart devices is indispensable to keep data privacy and security. However, conventional authentication methods are not applicable for wearables due to constraints of size and hardware, which makes present wearable devices lack convenient, secure, and low-cost authentication schemes. As a result, our team has conduct research on this topic and have proposed several novel authentication methods based on ubiquitous acoustic sensors. For more details, please refer to the following publications.
Papers: [Ubicomp'18][PerCom'20]
Demos: [BiLock]

With the rising popularity of smart earphones recently, they open up a new world for users to enjoy music individually, but also bring about privacy concerns at the same time. Existing few research works share shortcomings of intrusiveness to users, high power consumption, and purely focusing on authentication. Instead, in this paper, we propose a passive sensing system called EarID with low-cost customized earphones which attains user authentication and identification at once. For more details, please refer to the following publications.
Papers: [TMC'21]
Demos: [EarID]

Strength training is becoming popular among all age groups, as it helps participants increase muscle strength, improve body flexibility, reduce health risks and reshape physical forms. However, strength training imposes strict regulations on gestures and requires professional instruction in real time for the sake of body-building efficiency and safety. We propose a novel low-cost system named iCoach, to provide real-time monitoring and coaching service for strength training participants. For more details, please refer to the following publications.
Papers: [IOTJ'20]
Demos: [iCoach]

The increasing popularity of earable devices stimulates great academic interest to design novel head gesture-based interaction technologies. But existing works simply consider it as a singular activity recognition problem. This is not in line with practice since users may have different body movements such as walking and jogging along with head gestures. We propose a method to recognize composite head-body activities with a single IMU sensor based on multi-task learning network. For more details, please refer to the following publications.
Papers: [PerCom'23]
Demos: [EarMotion]