A machine learning model for predicting sit-to-stand trajectories of people with and without stroke: towards adaptive robotic assistance (2022)
Journal Article
Bennett, T., Kumar, P., & Ruiz Garate, V. R. (2022). A machine learning model for predicting sit-to-stand trajectories of people with and without stroke: towards adaptive robotic assistance. Sensors, 22(13), https://doi.org/10.3390/s22134789

Sit-to-stand and stand-to-sit transfers are fundamental daily motions that enable all other types of ambulation and gait. However, the ability to perform these motions can be severely impaired by different factors, such as the occurrence of a stroke,... Read More about A machine learning model for predicting sit-to-stand trajectories of people with and without stroke: towards adaptive robotic assistance.

Role of assistive devices in rehabilitation of people with stroke (2022)
Presentation / Conference
Kumar, P. (2022, June). Role of assistive devices in rehabilitation of people with stroke. Presented at Assistive Tech workshop, Bristol Robotics Laboratory, Bristol Robotics Laboratory, UWE

This presentation provides an overview on role of assistive devices - Lycra Arm sleeves/accelerometers/ GripAble Gaming Device for the rehabilitation of upper limb function in people with stroke. Of the 80% of people with stroke who lose upper-l... Read More about Role of assistive devices in rehabilitation of people with stroke.

Automatic report-based labelling of clinical EEGs for classifier training (2022)
Conference Proceeding
Western, D., Weber, T., Kandasamy, R., May, F., Taylor, S., Zhu, Y., & Canham, L. (2022). Automatic report-based labelling of clinical EEGs for classifier training. In 2021 IEEE Signal Processing in Medicine and Biology Symposium (SPMB). https://doi.org/10.1109/SPMB52430.2021.9672295

Machine learning classifiers for detection of abnormal clinical electroencephalography (EEG) signals have advanced signficantly in recent years, largely supported by the carefully curated Temple University Hospital Abnormal EEG Corpus (TUAB). Further... Read More about Automatic report-based labelling of clinical EEGs for classifier training.