In spite of the availability of ECMO equipment during the COVID-19 pandemic, many hospitals were unable to use it due to a lack of skilled staff. This paper reports on the effectiveness of HFM on assembling ECMO. This manual uses augmented reality (AR), smart glasses (SG), and a voice recognition system to enable operators to operate page through the manual, allowing them to view the object being operated and the manual in the same field of view. Results of previous studies suggest that medical technicians who have practiced with paper manuals at least once can successfully operate equipment using hands-free manuals (HFM). Therefore, participants were asked to practice operating the device using a conventional paper manual (practice) and to operate the device using the HFM one week later (test). Participants were asked to rate (1) the accuracy of the operation, (2) the time it took them to successfully operate the device, and (3) to complete a questionnaire. Participants were clinical engineers and nurses (8 males and 2 females). Although some operational errors were observed during the practice, all participants successfully performed the operation during the test, although it took more time and effort. Participants offered suggestions for improvement to the SG.

Ophthalmic diseases, such as glaucoma, which can cause visual impairments, increase with aging, and eye drop treatments are necessary to maintain visual function. However, more people than expected, particularly the elderly and those with neck or arm disabilities, have difficulty using eye drops. This study aims to develop an automatic eye drop device that allows users to keep their face forward while delivering a droplet to the eye positioned diagonally downward using lateral force generated by horizontal airflow. The influence on eye drop probability was discussed based on the ±3σ range of trajectory variations calculated from the mean and standard deviation of droplet weights, and the differences in eyelid holding methods. The eye drop probability without holding the eyelids was 81%. When both the upper and lower eyelids were opened with fingers, and when looking up at the LED fixation light, the probabilities were 100% for both. This method of looking up at an LED fixation light without holding the eyelids is suitable for administering a droplet from a diagonal angle and excels in terms of hygiene.

In this study, malfunctions of mechanical ventilators were categorized into internal and external factors, with the objective of analyzing each type of malfunction using text mining. The data used in this study consisted of malfunction reports of mechanical ventilators published between 2010 and 2023 by the Ministry of Health, Labour and Welfare and the Japan Council for Quality Health Care. The number of reported malfunctions included 2,864 cases of medical device malfunction reports, 1,984 near-miss incidents, and 255 cases of medical accident information. The analysis revealed that internal factors included hardware and software failures as well as technical malfunctions. Malfunctions related to external factors were commonly reported in relation to routine operations, procedural errors, human errors, and patient condition management. Specific malfunctions reported in near-miss incidents involved equipment setting errors and attachment issues, while malfunctions related to alarms and emergency responses were reported in medical accident information.