This dataset contains still thermal frames from thirty patients undergoing awake craniotomy for brain tumor resection. The data were used as part of a study on automated craniotomy masking, where the portion of the craniotomy image which contans the brain is identified. The data contains manually generated gold-standard masks, as well as masks created with the proposed method in "Automated Craniotomy Masking for Intraoperative Thermography".

Supplementary video for the article "A Programmable CMOS DEP Chip for Cell Manipulation"

This video demonstrates the use of a CMOS DEP chip for particle manipulation, including particle patterning, concentration control, and single particle manipulation, all performed on the same chip and sample.

Seismocardiography (SCG) Signal Processing Dataset is a comprehensive collection of data samples to simulate the real-world application of the advanced technique in cardiac health monitoring. The dataset has been collected in different medical conditions of the patient in a real-time medical environment at varying timestamps. This dataset contains 1,000 samples collected over a period from 10 November 2023 to 10 January 2024, providing a robust timeframe in various conditions.

Chronic wounds pose an ongoing health concern globally, largely due to the prevalence of conditions such as diabetes and leprosy's disease. The standard method of monitoring these wounds involves visual inspection by healthcare professionals, a practice that could present challenges for patients in remote areas with inadequate transportation and healthcare infrastructure. This has led to the development of algorithms designed for the analysis and follow-up of wound images, which perform image-processing tasks such as classification, detection, and segmentation.