Healing hands
Disciplines
Engineering | Medicine and Health Sciences
Abstract (300 words maximum)
Continuous and noninvasive patient monitoring is needed in healthcare and ER settings to make sure solutions to problems are addressed quickly and correctly. However, existing monitoring systems often rely on multiple discrete devices, resulting in fragmented data collection and increased complexity for patients and healthcare providers such as nurses or doctors. This project addresses the need for an integrated, intelligent monitoring solution by developing "Healing Hands," a pair of robotic end effector hands designed to seamlessly incorporate various patient monitoring technologies and novel sensors. Healing Hands seek to integrate a comprehensive array of advanced sensors for thorough patient monitoring. These include sensitive ECG pads and custom-developed sensors for precise cardiac monitoring, photonic-based oxygen meters and heart rate. The fingertips will equip ultrasound transducers for non-invasive diagnostic imaging. This seamless integration of diverse sensing technologies ensures a holistic approach to continuous patient health monitoring. These hands are designed to attach to an existing humanoid robot unit, which utilizes artificial intelligence systems, including large language models (LLMs), to interpret and validate the collected data, providing real-time analysis and alerts. The proposed solution offers a unified platform for continuous patient monitoring, reducing the need for multiple devices and simplifying the monitoring process. By leveraging AI-driven data analysis, Healing Hands can infer critical health indicators, detect anomalies, and facilitate proactive healthcare interventions. The expected outcome of this research is the development of fully functional holistic sensing Healing Hands capable of providing comprehensive and continuous monitoring to enhance patient care through integrated, real-time data collection and intelligent analysis, ultimately contributing to improved healthcare outcomes and operational efficiency in medical settings.
Academic department under which the project should be listed
SPCEET - Robotics and Mechatronics Engineering
Primary Investigator (PI) Name
Razvan Voicu
Healing hands
Continuous and noninvasive patient monitoring is needed in healthcare and ER settings to make sure solutions to problems are addressed quickly and correctly. However, existing monitoring systems often rely on multiple discrete devices, resulting in fragmented data collection and increased complexity for patients and healthcare providers such as nurses or doctors. This project addresses the need for an integrated, intelligent monitoring solution by developing "Healing Hands," a pair of robotic end effector hands designed to seamlessly incorporate various patient monitoring technologies and novel sensors. Healing Hands seek to integrate a comprehensive array of advanced sensors for thorough patient monitoring. These include sensitive ECG pads and custom-developed sensors for precise cardiac monitoring, photonic-based oxygen meters and heart rate. The fingertips will equip ultrasound transducers for non-invasive diagnostic imaging. This seamless integration of diverse sensing technologies ensures a holistic approach to continuous patient health monitoring. These hands are designed to attach to an existing humanoid robot unit, which utilizes artificial intelligence systems, including large language models (LLMs), to interpret and validate the collected data, providing real-time analysis and alerts. The proposed solution offers a unified platform for continuous patient monitoring, reducing the need for multiple devices and simplifying the monitoring process. By leveraging AI-driven data analysis, Healing Hands can infer critical health indicators, detect anomalies, and facilitate proactive healthcare interventions. The expected outcome of this research is the development of fully functional holistic sensing Healing Hands capable of providing comprehensive and continuous monitoring to enhance patient care through integrated, real-time data collection and intelligent analysis, ultimately contributing to improved healthcare outcomes and operational efficiency in medical settings.