Smart Hospital Robot With Embedded Sensors For Automated Patient Data Logging To EMR Systems
DOI:
https://doi.org/10.29284/ijasis.12.1s.2026.58-73Keywords:
EMR, Robot / Robotics, Automation, Health, Embedded sensor, Patient data, Patient record, Latency, Accuracy, Efficiency, Interoperability / HL7 / FHIR, Clinical workflow.Abstract
This paper is a report detailing a smart hospital robot, which is designed, developed and evaluated to record patient data automatically through embedded sensors into the Electronic Medical Record (EMR) systems. The robot incorporates biosensors of heart rate, blood pressure, oxygen saturation, and temperature with a clinical level of accuracy of ±2 bpm, ±3 mmHg, and ±0.2°C. System reliability testing showed 99.2 % uptime during 500 hours, and the system was able to autonomously operate for 14 hours per charge. EMR logging performance was significantly enhanced, as the average latency was 1.8 seconds and throughput amounted to 120 records of patients per hour, in comparison with 25 records/hour with paper records. Trial navigation had up to 98.9% success rate in reaching patient beds, obstacle detection in under 0.3 seconds, and path deviation in less than 5 cm. Comparative analysis showed robotic logging used half an hour to enter data compared to manual input, with a 90 % reduction in documentation errors and a 93 % error reduction. The results of the user interaction studies conducted with 40 clinicians demonstrated that 87% of them were positively accepted, and the integration of the workflow decreased the cognitive burden and allocated 32% more time to patient care. Although the results also confirm that substantial gains have been made regarding accuracy, efficiency, and workflow optimization, three key issues are problematic in terms of fault tolerance, contextual adaptability, and cybersecurity. The findings support the power of robotic patient-monitoring systems to promote digital transformation in healthcare, as well as to show where the innovations could be improved in the future and undergo clinical validation.
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