COVID-19パンデミックの際，ECMO機器が利用可能であったにもかかわらず，多くの病院では熟練したスタッフの不足により使用できなかった．本稿では，ECMOの組み立てにおけるハンズフリーマニュアル（HFM）の有効性について報告する．このマニュアルは，拡張現実感（AR），スマートグラス（SG），音声認識システムを用いて，オペレータがマニュアルのページを操作できるようにしたもので，操作対象とマニュアルを同じ視野で見ることができる．先行研究の結果から，紙のマニュアルで一度でも練習したことのある医療技術者は，HFMを使用して機器をうまく操作できることが示唆されている．そこで，参加者には，従来の紙マニュアルを用いて機器の操作を練習してもらい（練習），１週間後にHFMを用いて機器を操作してもらった（テスト）．参加者には，（１）操作の正確さ，（２）操作が成功するまでに要した時間，（３）アンケートへの回答を求めた．参加者は臨床工学技士と看護師（男性８名，女性２名）であった．実習では操作ミスが散見され，本試験では時間と労力がかかったものの，参加者全員が操作を成功させた．参加者からは，SGに対する改善提案があった．

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.