Demo Data from EDBT 2026 / reviewers in the wild / expert
Chih-Yun Liu
dblp:66/1802
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1Human-computer interaction and ubiquitous computing · 1Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Wearable and physiological sensing · 77% Health and well-being technologies · 23% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wearable and physiological sensing › motion sensing
wearable motion sensing |
0.3 | 1 | 2018 | SaFePlay+: A Wearable Cycling Measurement and Analysis System of Lower Limbs · MobiCom 2018 |
Methods — techniques the papers use, named apart from their topics
wearable power analyzer · 0.3pressure sensing insole · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | SaFePlay+: A Wearable Cycling Measurement and Analysis System of Lower LimbsabstractDifferent from the ordinary apparatus and plug-in devices on bikes, this research brings up a novel system called SaFePlay+, Smart Footwear Platform Plus. The system includes a pair of knee motion sensing module and smart pressure and motion sensing insole, analyzed module and interactive App. SaFePlay+ can immediately collect lower limbs information of users. Moreover, through the novel algorithm of wearable power analyzer, it can help users to understand their body condition in order to adjust the posture, raise the efficiency and avoid sports injury. Through the verification of the apparatus, it shows that our method can get good cadence and power performance. Tse-Yu Lin, Shih-Yao Wei, Heng-Yi Chen, Li-Yang Huang, Chih-Yun Liu, An-Chun Chen, Yin-Yu Chou, Hsing-Mang Wang |
MobiCom | 5 |
| 2013 | A Body-Sensed Motor Assessment System for Stroke Upper-Limb Rehabilitation: A Preliminary StudyabstractBased on the clinic data, 69 % - 80 % stroke patients in Taiwan have the muscle weakness symptom of upper limb. Stroke patients are able to restore their independent living if they keep formal rehabilitation without interruption. However, due to the tedious and painful process, stroke patients may pause or suspend their rehabilitation therapy. Moreover, physiatrists in Taiwan hospitals must take care of more than one patient at the same time. This paper is motivated to propose a motor assessment system for stroke upper-limb rehabilitation. Our implementation is integrated with the Complete Minnesota Dexterity Test to quantify patients' recovery status automatically. Therefore, our implementation is able to reduce the workload of physiatrists effectively. In addition to assessment scale score, the proposed system is able to record more details, e.g., the tremor status and the grip strength, for doctors to evaluate the following rehabilitation therapy. Finally, a body-sensed game is provided to increase interest to the rehabilitation process. Chao-Hsien Lee, Yu-Hsien Chiu, Hao-Yun Kao, I-Te Chen, I-Nong Lee, Wen-Hsien Ho, Pin-Han Huang, Sin-Hao Chen, Chih-Yun Liu, Hsiao-Yan Lu |
SMC | 10 |