300.000 DKK grant from Helsefonden
Professor Ole Rahbek has received a 300.000 DKK grant from Helsefonden to sensor-based gait monitoring at home after knee replacement surgery.
Over the last few years, artificial intelligence (AI) has made significant development in the field of telemedicine and monitoring patients. Wearable sensors are nowadays smaller and simpler than ever and can provide us with real-time and comprehensive data regarding the patients’ health and function. The objective of this project is to discover and develop methods for monitoring patients after knee replacement surgery by using sensor-based gait analysis utilizing machine learning and biomechanical modeling of the gait.
This project develops an innovation in home monitoring of recovery after knee arthroplasties based on advanced portable sensor technologies and motion analysis, which can also be applied to other surgeries in future. This remote monitoring system can measure the quantity and quality of patients' gait and motion as parameters that support clinical decision-making during recovery and postoperative period. By establishing a practical system to continuously monitor the course of recovery after surgery, the patients would get a faster and more secure recovery. The risk of serious and threatening complications will reduce, as timely detection of complications leads to proper treatment.
Over the last few years, artificial intelligence (AI) has made significant development in the field of telemedicine and monitoring patients. Wearable sensors are nowadays smaller and simpler than ever and can provide us with real-time and comprehensive data regarding the patients’ health and function. The objective of this project is to discover and develop methods for monitoring patients after knee replacement surgery by using sensor-based gait analysis utilizing machine learning and biomechanical modeling of the gait.
This project develops an innovation in home monitoring of recovery after knee arthroplasties based on advanced portable sensor technologies and motion analysis, which can also be applied to other surgeries in future. This remote monitoring system can measure the quantity and quality of patients' gait and motion as parameters that support clinical decision-making during recovery and postoperative period. By establishing a practical system to continuously monitor the course of recovery after surgery, the patients would get a faster and more secure recovery. The risk of serious and threatening complications will reduce, as timely detection of complications leads to proper treatment.