Publications by authors named "D M J B Senanayake"
Background: Inter-segment joint angles can be obtained from inertial measurement units (IMUs); however, accurate 3D joint motion measurement, which requires sensor fusion and signal processing, sensor alignment with segments and joint axis calibration, can be challenging to achieve.
Research Question: Can an artificial neural network modeling framework be used for direct, real-time conversion of IMU data to joint angles during walking and running, and how does sensor number, location on the body and gait speed impact prediction accuracy?
Methods: Thirty healthy adult participants performed gait experiments in which kinematics data were obtained from self-placed IMUs and video motion analysis, the reference standard for joint kinematics. Data were collected during walking at 0.
Article Synopsis
- Scientists created a new tool called IL-VIS that helps track and show changes in experiments over time, instead of just showing one moment.
- IL-VIS learns from the data as new information comes in and gives a clear picture of how things are changing, which is better than older methods.
- The researchers tested IL-VIS with both fake and real data from brain organoids to see how they reacted to a substance related to diseases like Alzheimer's, finding important information about their development and reactions.
Article Synopsis
- DXA scans are commonly used to measure bone mineral density, but they're rarely utilized for assessing fracture risk.
- The study aimed to integrate deep learning techniques with DXA images and clinical data to determine fracture risk in adults who have experienced falls and matched healthy controls.
- A model was developed using advanced neural networks, achieving a 74.3% average score in predicting fracture risk, showing promise for future screening tools for older adults at risk of falling.
Advances in sequencing technologies and declining costs are increasing the accessibility of large-scale biodiversity genomic datasets. To maximize the impact of these data, a careful, considered approach to data management is essential. However, challenges associated with the management of such datasets remain, exacerbated by uncertainty among the research community as to what constitutes best practices.
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