Welcome to the homepage of MAASC (Medical Alarm Audibility System Checker), a software tool for checking whether medical alarms within a modeled configuration can ever be rendered inaudible due to simultaneous masking between concurrently sounding medical alarm. MAASC will also allow analysts to check whether a given alarm configuration is consistent with the IEC 60601-1-8 international medical alarm standard.

MAASC was created in the Formal Human Systems Laboratory at the University at Buffalo, the State University of New York under the supervision of Dr. Matthew L. Bolton with software development and documentation from Thomas Darget and Elliot Biltekoff. This tool was created as part of a larger project sponsored by the Agency for Healthcare Research and Quality () under award number R18HS024679. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality.

License

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Download

MAASC is a Java desktop application that is compatible with both MS Windows and Linux desktops (thought a 64 bit Linux environment is highly recommended).

You can download the latest version of MAASC here: MAASC v2.0

This file can be double clicked on to run once the dependencies (see below) have been installed.

Dependencies

MAASC requires the following additional software to run correctly:

Java: MAASC is a Java software and requires the presence of a Java virtual machine. Java installation and instructions can be found at https://www.java.com/

Cygwin (Windows only): Running MAASC on windows requires the 32-bit version of Cygwin (the 64-bit version is currently not supported).

SAL: MAASC makes use of the Infinite Bounded Model Checker (sal-inf-bmc) which is part of the Symbolic Analysis Laboratory (SAL). Installation files for SAL can be found at the following (installation instructions can be found in the INSTALL.txt in the below archives):

64 Bit Linux

32 Bit Linux

Windows (special instructions for installing SAL on Windows can be found here)

Documentation

Information on configuring and running mask can be found in the following:

Frequently Asked Questions (FAQ)

Tutorial

Contact and Feedback

Questions, feedback, and feature requests can be sent to Dr. Matthew L. Bolton (mbolton[at]buffalo[dot]edu)

Related Research Papers

MAASC was created as part of a larger research project. Papers describing the science underlying MAASC can be found in all of the following papers:

Bolton, M. L.C, Zheng, X., Li, M., Edworthy, J. R., Boyd, A. D., (N.D.). An Experimental Validation of Masking in IEC 60601-1-8:2006-Compliant Alarm Sounds. In Press, Human Factors, DOI: 10.1177/0018720819862911 20 pages.

Edworthy, J. R., McNeer, R. R., Bennett, C. L., Dudaryk, R., McDougall, S. J. P., Schlesinger, J. J., Bolton, M. L., Edworthy, J. D., Vieira, E. O., Boyd, A. D., Reid, S. K. J., Rayo, M. F., Wright, M. C., & Osborn, D. (ND). Getting alarm sounds into a global standard. Accepted to Ergonomics in Design, 26(2), 4-13.

Bolton, M. L., Edworthy, J., Boyd, A. D., Wei, J., & Zheng, X. (2018). A computationally efficient formal method for discovering masking in concurrently sounding medical alarms. Accepted to Applied Acoustics, 141, 403-415.

Hasanain, B., Boyd, A. D., & Bolton, M. L. (2017). A Formal Approach to Discovering Simultaneous Additive Masking Between Auditory Medical Alarms. Applied Ergonomics, 58, 500-514.

Hasanain, B., Boyd, A. D., & Bolton, M. L. (2016). Using model checking to detect simultaneous masking in medical alarms. IEEE Transactions on Human-Machine Systems, 46(2), 174 - 185.

Bolton, M. L., Edwothy, J., & Boyd, A. D. (2018). A Formal Analysis of Masking Between Reserved Alarm Sounds of the IEC 60601-1-8 International Medical Alarm Standard. Proceedings of the 2018 International Annual Meeting of the Human Factors and Ergonomics Society (pp. 523-527). Santa Monica: HFES.

Bolton, M. L., Hasanain, B., Boyd, A. D., & Edwothy, J. (2016). Using model checking to detect masking in IEC 60601-1-8-compliant alarm configurations. Proceedings of the 2016 International Annual Meeting of the Human Factors and Ergonomics Society (pp. 636-640). Santa Monica: Human Factors and Ergonomics Society.