Vision-Based Method for Automatic Quantification of Parkinsonian Bradykinesia.

Non-volitional discontinuation of motion, namely bradykinesia, is a common motor symptom among patients with Parkinson's disease (PD). Evaluating bradykinesia severity is an important part of clinical examinations on PD patients in both diagnosis and monitoring phases. However, subjective evaluations from different clinicians often show low consistency. The research works that explore objective quantification of bradykinesia are mostly based on highly-integrated sensors. Although these sensor-based methods demonstrate applaudable performance, it is unrealistic to promote them for wide use because the special devices they require are far from popularized in daily lives. In this paper, we take advantage of computer vision and machine learning technologies, proposing a vision-based method to automatically and objectively quantify bradykinesia severity. Three bradykinesia-related items are investigated in our study: finger tapping, hand clasping and hand pro/supination. In our method, human pose estimation technology is utilized to extract kinematic characteristics and supervised-learning-based classifiers are employed to generate score ratings. Clinical experiment on 60 patients shows that the scoring accuracy of our method over 360 examination videos is 89.7%, which is competitive with other related works. The devices our method requires are only a camera for instrumentation and a laptop for data processing. Therefore, our method can produce reliable assessment results on Parkinsonian bradykinesia with minimal device requirement, showing great potential of realizing long-term remote monitoring on patients' condition.

Improvement on the Fatigue Performance of 2024-T4 Alloy by Synergistic Coating Technology.

In this paper, rotating bending fatigue tests of 2024-T4 Al alloy with different oxide coatings were carried out. Compared to the uncoated and previously reported oxide coatings of aluminum alloys, the fatigue strength is able to be enhanced by using a novel oxide coating with sealing pore technology. These results indicate that the better the coating surface quality is, the more excellent the fatigue performance under rotating bending fatigue loading is. The improvement on the fatigue performance is mainly because the fatigue crack initiation and the early stage of fatigue crack growth at the coating layer can be delayed after PEO coating with pore sealing. Therefore, it is a so-called synergistic coating technology for various uses, including welding thermal cracks and filling micro-pores. The effects of different oxide coatings on surface hardness, compressive residual stress, morphology and fatigue fracture morphology are discussed. A critical compressive residual stress of about 95-100 MPa is proposed.