Robot coupled to system information can acquire data from patients in unprecedented ways. They can use sensors to provide the physiologic status of the patient, engage the patient in physical interaction in order to acquire external measure of the health such as strength, interact with the patient in social ways to acquire behavioral data, such as eye gaze, gesture, joint attention, etc, more repeatedly and objectively than a human observer could. The robot can be made aware of the history of the particular health condition and its treatment, and be informed by sensors of the interaction that occur between the patient and the physician or caregivers. Quantitative diagnosis and assessment requires sensing of the patient, application of stimuli to gauge responses, and the intelligence to use the acquired data for assessment and diagnosis. When diagnosis or assessment is uncertain, the robot can be directed to acquire more appropriate data. The robot should be able to interact with the caregiver or physician to help them to make a diagnosis or assessment with sophisticated domain knowledge. As robots facilitate aging in place e.g. in the home, automated assessment becomes more important as a means to alert a caregiver, who may not always be present, about potential health problems.
Many technological components related to assessment and diagnosis, such as micro electromechanical lab on a chip sensor for chemical analysis and smart clothing that records heart rate and other physiologic phenomena, borrow from ideas in the field of the robotics or have been used by the robots in assessment and diagnosis. Others, such as using intelligent socially assistive robots to quantify behavioral data, are novel entirely and present new ways of treating data that had, to date, been only qualitative. The myriad steps in assessment and diagnosis need to each be improved and then combined into a seamless process.
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