This research investigates smart office chairs that monitor posture and provide real-time feedback to reduce pain and improve ergonomics. By comparing different feedback methods, the study evaluates whether timely reminders can effectively change behavior. The goal is to enhance workplace health while maintaining productivity in increasingly sedentary environments.

This research addresses excessive false alarms in hospital medical devices, which burden staff and distress patients. By detecting and filtering noisy data, the proposed system prevents false alerts while preserving true ones. Early results show complete removal of false alarms, improving efficiency, patient experience, and clinical response in healthcare settings.

This research highlights the limitations of current food safety detection and introduces nanoparticle-based smart packaging. These nanosensors detect gases from spoilage and signal safety through colour changes. By replacing guesswork with real-time indicators, this approach could prevent foodborne illness, improve consumer confidence, and modernise food safety in an increasingly technological world.

This research develops a spatial “GPS” for lung cancer screening by mapping CT scans into a shared coordinate system. By identifying high-risk regions for malignant nodules, it supports radiologists and AI in improving diagnostic accuracy, decision-making, and interpretability, transforming screening from broad search to targeted, data-driven precision.

This research presents a new fractional mathematical model for cardiovascular dynamics that maintains the accuracy of traditional methods while greatly reducing complexity. Using only five interpretable parameters instead of twenty, the model analyzes blood pressure in the frequency domain, providing clearer insight into heart function and offering potential improvements for diagnosis and treatment.

This research examines how AI is used in NHS radiology and challenges claims that it will replace radiologists. Instead of full automation, AI supports clinicians, helping manage workforce shortages while radiologists retain responsibility for diagnosis and treatment decisions. Evidence, not hype, should guide debates about AI and work.