OBJECTIVES: The purpose of this study was to develop an interactive software package of alarm sounds to present, recognize and share problems about alarm sounds among medical staff and medical manufactures. METHODS: The alarm sounds were recorded in variable alarm conditions in a WAV file. The alarm conditions were arbitrarily induced by modifying attachments of various medical devices. The software package that integrated an alarm sound database and simulator was used to assess the ability to identify the monitor that sounded the alarm for the medical staff. RESULTS: Eighty alarm sound files (40MB in total) were recorded from 41 medical devices made by 28 companies. There were three pairs of similar alarm sounds that could not easily be distinguished, two alarm sounds which had a different priority, either low or high. The alarm sound database was created in an Excel file (ASDB.xls 170 kB, 40 MB with photos), and included a list of file names that were hyperlinked to alarm sound files. An alarm sound simulator (AlmSS) was constructed with two modules for simultaneously playing alarm sound files and for designing new alarm sounds. The AlmSS was used in the assessing procedure to determine whether 19 clinical engineers could identify 13 alarm sounds only by their distinctive sounds. They were asked to choose from a list of devices and to rate the priority of each alarm. The overall correct identification rate of the alarm sounds was 48%, and six characteristic alarm sounds were correctly recognized by beetween 63% to 100% of the subjects. The overall recognition rate of the alarm sound priority was only 27%. CONCLUSIONS: We have developed an interactive software package of alarm sounds by integrating the database and the alarm sound simulator (URL: http://info.ahs.kitasato-u.ac.jp/tkweb/alarm/asdb.html ). The AlmSS was useful for replaying multiple alarm sounds simultaneously and designing new alarm sounds interactively.
OBJECTIVES: The purpose of this study was to develop an interactive software package of alarm sounds to present, recognize and share problems about alarm sounds among medical staff and medical manufactures. METHODS: The alarm sounds were recorded in variable alarm conditions in a WAV file. The alarm conditions were arbitrarily induced by modifying attachments of various medical devices. The software package that integrated an alarm sound database and simulator was used to assess the ability to identify the monitor that sounded the alarm for the medical staff. RESULTS: Eighty alarm sound files (40MB in total) were recorded from 41 medical devices made by 28 companies. There were three pairs of similar alarm sounds that could not easily be distinguished, two alarm sounds which had a different priority, either low or high. The alarm sound database was created in an Excel file (ASDB.xls 170 kB, 40 MB with photos), and included a list of file names that were hyperlinked to alarm sound files. An alarm sound simulator (AlmSS) was constructed with two modules for simultaneously playing alarm sound files and for designing new alarm sounds. The AlmSS was used in the assessing procedure to determine whether 19 clinical engineers could identify 13 alarm sounds only by their distinctive sounds. They were asked to choose from a list of devices and to rate the priority of each alarm. The overall correct identification rate of the alarm sounds was 48%, and six characteristic alarm sounds were correctly recognized by beetween 63% to 100% of the subjects. The overall recognition rate of the alarm sound priority was only 27%. CONCLUSIONS: We have developed an interactive software package of alarm sounds by integrating the database and the alarm sound simulator (URL: http://info.ahs.kitasato-u.ac.jp/tkweb/alarm/asdb.html ). The AlmSS was useful for replaying multiple alarm sounds simultaneously and designing new alarm sounds interactively.