Matthew Moore
Papers
2
Total Citations
247
H-Index
2
About
Matthew Moore is a researcher whose work bridges the critical intersection of surgical innovation and geriatric assistive technology. His most impactful contribution lies in the field of thoracic surgery, where his landmark 2013 study, "Comparing robot-assisted thoracic surgical lobectomy with conventional video-assisted thoracic surgical lobectomy and wedge resection," analyzed data from the Premier multihospital database. This highly cited work (231 citations) provided crucial comparative evidence on the outcomes of robotic versus video-assisted techniques for lung cancer surgery, helping to shape clinical decision-making in minimally invasive thoracic procedures. More recently, Moore has turned his attention to the pressing challenge of elderly fall detection, a major health risk for aging populations. In his 2021 paper, he introduced a novel collaborative fall detection system that integrates a wearable device with a companion robot. This innovative approach leverages the strengths of both technologies to improve detection accuracy and response times for older adults aging in place. By combining rigorous clinical database analysis with cutting-edge human-robot interaction design, Moore demonstrates a unique ability to address complex health problems across the surgical and geriatric care spectrum, making his work relevant to both practicing clinicians and researchers in assistive robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Collaborative Fall Detection using a Wearable Device and a Companion Robot16 citations · 2021