I am a third-year student majored in Computer Science from the Department of Computer Science and Engineering (CSE) at the State University at Buffalo (UB). As a student member in the Embedded Sensing and Computing (ESC) lab at UB guided by Dr. Wenyao Xu, my research interests focus on Wearable Ecosystem and Pervasive Health.
Microsoft Office (Word, Excel, PowerPoint) MATLAB SketchUp Visio
Bilingual in English and Chinese Jogging Hiking
♦ Interaction Proxies Development
The interaction proxy is an advance technique for improving smartphone application's accessibility. By inserting the interaction proxy between the manifest and the original app interfaces, the visual elements (e.g., layouts, fonts, buttons, etc.) of applications can be modified. My current focus is developing interaction proxies for retrofitting kid's ebooks and games. The goal is to increase the accessibility for junior users with intellectual disability.
♦ Smartphone Application for Rehabilitation
The BigTabTablecloth application is designed specifically for assessments and managements in the rehabiliatation. The app challenges patients' motor control ability by setup a unique series of lights. Users need to touch the green light to turn it off. This app allows physicians and patients adjust many gaming attributes, including the sequence, the size, the color, the time limit and more. Game results (the location and the time of each touch on the screen, the time gap between actions, etc.) and the patient's physical information will be saved in output files for health-related purposes.
♦ Wearable Sensing Device Based Biofeedback System
One balance assessment, Timed Up and Go (TUG), has been widely applied to estimate the fall risk. However, operations in the control clinical setting make the TUG falling short of representing challenges in home and community environments that many seniors navigate. Having information on the motor performance in more complex environments can better inform clinicians about an individual's risk of falling. Smart Insole TUG is an advanced system suitable for the TUG with complex environmental factors. The system consists of a wearable sensing device (Smart Insole), a TUG data analysis module (four refined aspects in the gait feature and six detailed phases in the TUG process), and a matched smartphone software (real-time test results).
♦ Conference Proceedings Paper
Zhuolin Yang, Chen Song, Feng Lin, Jeanne Langan, Wenyao Xu, "Empowering a Gait Feature-Rich Timed-Up-and-Go System for Complex Ecological Environments", accepted by Second IEEE Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE 2017), Philadelphia, USA, July 2017.
♦ Demo/Poster Paper
Zhuolin Yang, Feng Lin, Wenyao Xu, Jeanne Langan, Lora Cavuoto, Zhinan Li, Qin Li, "Validation of a Novel Gait Analysis System", accepted by Second IEEE Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE 2017), Philadelphia, USA, July 2017.
♦ Poster Presentation
Zhuolin Yang, Feng Lin, Wenyao Xu, "Smart Insole TUG: an Advanced Timed-Up-and-Go System for Fall Risk Analysis Based on Wearable Sensor Device", accepted by Celebration of Student Academic Excellence, SUNY UB, April 2017.
♦ Excellent in Research (Spring 2017)
♦ Dean's List (Fall 2015)
♦ Top Student Award (2011 - 2012)
♦ Mathematic Contest of Guangdong (2010)
- Third Prize (Provincial Level)