Healthcare robots struggle to protect patient privacy in real-world conditions
Researchers tested whether service robots can safely mask patients' faces while working in doctor's offices. The technology works in controlled settings but fails when patients move, lighting changes, or they're partially hidden—raising questions about robot deployment in hospitals before the privacy problem is solved.
Originaltitel: The Privacy-Preserving Capabilities of a Service Robot in a Scenario-Based Healthcare Setting
As populations age and life expectancy rises, healthcare systems face growing staff shortages. Service robots have been proposed to support healthcare personnel, but their use introduces significant privacy challenges. This paper investigates whether a service robot can protect individuals’ privacy through face obfuscation while performing autonomous tasks in unconstrained healthcare environments. Our approach relies on a face recognition system trained to identify doctors and patients. Scenario-based experiments simulating a doctor’s office show that the system achieves partial success: non-target individuals are reliably obfuscated, and patients can be recognized when frontal views are available. However, real-world conditions such as pose variation, occlusion, and lighting changes reduce recognition reliability, limiting privacy protection. These results highlight both the potential and the current limitations of face obfuscation for privacy-preserving service robots, providing guidance for near-term deployment strategies in constrained interaction scenarios.