Transfer learning helps wearable sensors classify gait phases more accurately and efficiently
Peer-Reviewed Publication
Updates every hour. Last Updated: 29-Oct-2026 16:16 ET (29-Oct-2026 20:16 GMT/UTC)
A new study in Artificial Intelligence and Autonomous Systems shows that neural networks pre-trained to predict continuous gait cycle progression can be reused to improve gait phase classification from foot-mounted inertial sensor data. The approach achieved an F1-score of 0.9788, CPU inference latency below 0.07 ms with a compact DNN, and 92.3% accuracy on an independent young-adult dataset.
In new research, Yan Leng, assistant professor of information, risk, and operations management at the McCombs School of Business at The University of Texas at Austin, has devised a sort of personality test — more precisely, a behavioral audit — for large language models (LLMs), the technology that drives products such as ChatGPT.
By understanding an LLM’s existing tendencies, an organization can decide whether an available model already fits its values and usage scenarios. If not, it might need to fine-tune a model before putting it to use.
Leng compares her framework to trying to understand a person through their actions and thought processes. “For a human, we would have our values, and our values would dictate how we make decisions, so we try to have that for LLMs as well,” she says.
Creative Destruction Lab (CDL), a global nonprofit that supports science- and technology-based startups, today announced the launch of CDL-Cleveland in partnership with University Hospitals (UH) and Case Western Reserve University (CWRU). The new site will host the CDL Healthcare Delivery stream, focused on early-stage ventures building technology to reduce costs, improve patient outcomes, and accelerate the adoption of innovation inside real clinical environments.
U.S. is developing lithium mines to reduce reliance on foreign supply chains. New study assessed whether U.S. subbasins can support water-intensive lithium mining. Team combined water, climate and socioeconomic models to project water supply and demand between 2040 and 2060. Under every scenario, most western subbasins struggled to meet existing water demands, let alone support additional lithium mining.