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Published in: Journal of Clinical Monitoring and Computing 4/2020

01-08-2020 | Fatigue | Original Research

SAVIOR ICU: sonification and vibrotactile interface for the operating room and intensive care unit

Authors: Kendall J. Burdick, Seiver K. Jorgensen, Taylor N. Combs, Megan O. Holmberg, Samantha P. Kultgen, Joseph J. Schlesinger

Published in: Journal of Clinical Monitoring and Computing | Issue 4/2020

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Abstract

Alarm fatigue is an issue for healthcare providers in the intensive care unit, and may result from desensitization of overbearing and under-informing alarms. To directly increase the overall identification of medical alarms and potentially contribute to a downstream decrease in the prevalence of alarm fatigue, we propose advancing alarm sonification by combining auditory and tactile stimuli to create a multisensory alarm. Participants completed four trials—two multisensory (auditory and tactile) and two unisensory (auditory). Analysis compared the unisensory trials to the multisensory trials based on the percentage of correctly identified point of change, direction of change and identity of three physiological parameters (indicated by different instruments): heart rate (drums), blood pressure (piano), blood oxygenation (guitar). A repeated-measures of ANOVA yielded a significant improvement in performance for the multisensory group compared to the unisensory group (p < 0.05). Specifically, the multisensory group had better performance in correctly identifying parameter (p < 0.05) and point of change (p < 0.05) compared to the unisensory group. Participants demonstrated a higher accuracy of identification with the use of multisensory alarms. Therefore, multisensory alarms may relieve the auditory burden of the medical environment and increase the overall quality of care and patient safety.
Literature
1.
go back to reference Sendelbach S, Funk M. Alarm fatigue: a patient safety concern. AACN Adv Crit Care. 2013;24(4):378–86.PubMedCrossRef Sendelbach S, Funk M. Alarm fatigue: a patient safety concern. AACN Adv Crit Care. 2013;24(4):378–86.PubMedCrossRef
2.
go back to reference Couch C. How redesigning the abrasive alarms of hospital soundscapes can save lives. Couch C. How redesigning the abrasive alarms of hospital soundscapes can save lives.
3.
go back to reference Kit S. ECRI’s Top 10 Health Technology Hazards for 2013. Health Devices. 2013;41(11):342–65. Kit S. ECRI’s Top 10 Health Technology Hazards for 2013. Health Devices. 2013;41(11):342–65.
4.
go back to reference Casey S, Avalos G, Dowling M. Critical care nurses’ knowledge of alarm fatigue and practices towards alarms: a multicentre study. Intensive Crit Care Nurs. 2018;48:36–41.PubMedCrossRef Casey S, Avalos G, Dowling M. Critical care nurses’ knowledge of alarm fatigue and practices towards alarms: a multicentre study. Intensive Crit Care Nurs. 2018;48:36–41.PubMedCrossRef
5.
go back to reference Kristensen MS, Edworthy J, Özcan Vieira E, Denham S. Alarm fatigue in the perception of medical soundscapes. In: European congress and exposition on noise control engineering, 2015, pp. 745–50. Kristensen MS, Edworthy J, Özcan Vieira E, Denham S. Alarm fatigue in the perception of medical soundscapes. In: European congress and exposition on noise control engineering, 2015, pp. 745–50.
7.
go back to reference Purbaugh T. Alarm fatigue: a roadmap for mitigating the cacophony of beeps. Dimens Crit Care Nurs. 2014;33(1):4–7.PubMedCrossRef Purbaugh T. Alarm fatigue: a roadmap for mitigating the cacophony of beeps. Dimens Crit Care Nurs. 2014;33(1):4–7.PubMedCrossRef
8.
go back to reference Cropp AJ, Woods LA, Raney D, Bredle DL. Name that tone: the proliferation of alarms in the intensive care unit. Chest. 1994;105(4):1217–20.PubMedCrossRef Cropp AJ, Woods LA, Raney D, Bredle DL. Name that tone: the proliferation of alarms in the intensive care unit. Chest. 1994;105(4):1217–20.PubMedCrossRef
9.
go back to reference Hasanain B, Boyd AD, Bolton ML. Using model checking to detect simultaneous masking in medical alarms. IEEE Trans Hum–Mach Syst. 2016;46(2):174–85.CrossRef Hasanain B, Boyd AD, Bolton ML. Using model checking to detect simultaneous masking in medical alarms. IEEE Trans Hum–Mach Syst. 2016;46(2):174–85.CrossRef
10.
go back to reference Kramer G, et al. Sonification report: status of the field and research agenda. Lincoln: University of Nebraska; 2010. Kramer G, et al. Sonification report: status of the field and research agenda. Lincoln: University of Nebraska; 2010.
11.
go back to reference Janata P, Childs E. Marketbuzz: sonification of real-time financial data. Georgia Institute of Technology; 2004. Janata P, Childs E. Marketbuzz: sonification of real-time financial data. Georgia Institute of Technology; 2004.
12.
14.
go back to reference Fitch WT, Kramer G. Sonifying the body electric: superiority of an auditory over a visual display in a complex, multivariate system. In: Santa FE Institute Studies in the Sciences of Complexity—proceedings volume, vol. 18. Boston: Addison-Wesley Publishing Co; 1994, p. 307. Fitch WT, Kramer G. Sonifying the body electric: superiority of an auditory over a visual display in a complex, multivariate system. In: Santa FE Institute Studies in the Sciences of Complexity—proceedings volume, vol. 18. Boston: Addison-Wesley Publishing Co; 1994, p. 307.
15.
go back to reference Hermann T. Taxonomy and definitions for sonification and auditory display. In: Proceedings of the 14th international conference on auditory display (ICAD 2008), 2008. Hermann T. Taxonomy and definitions for sonification and auditory display. In: Proceedings of the 14th international conference on auditory display (ICAD 2008), 2008.
16.
go back to reference Ballora M, Pennycook B, Ivanov PC, Glass L, Goldberger AL. Heart rate sonification: a new approach to medical diagnosis. Leonardo. 2004;37(1):41–6.CrossRef Ballora M, Pennycook B, Ivanov PC, Glass L, Goldberger AL. Heart rate sonification: a new approach to medical diagnosis. Leonardo. 2004;37(1):41–6.CrossRef
17.
go back to reference Wang J. Emergency healthcare workflow modeling and timeliness analysis. IEEE Trans Syst Man Cybern A. 2012;42(6):1323–31.CrossRef Wang J. Emergency healthcare workflow modeling and timeliness analysis. IEEE Trans Syst Man Cybern A. 2012;42(6):1323–31.CrossRef
18.
go back to reference Kang Y, Li Z, Zhao Y, Qin J, Song W. A novel location strategy for minimizing monitors in vehicle emission remote sensing system. IEEE Trans Syst Man Cybern Syst. 2018;48(4):500–10.CrossRef Kang Y, Li Z, Zhao Y, Qin J, Song W. A novel location strategy for minimizing monitors in vehicle emission remote sensing system. IEEE Trans Syst Man Cybern Syst. 2018;48(4):500–10.CrossRef
19.
go back to reference Nunes VT, Werner CML, Santoro FM. Dynamic process adaptation: a context-aware approach. IEEE; 2011, pp. 97–104. Nunes VT, Werner CML, Santoro FM. Dynamic process adaptation: a context-aware approach. IEEE; 2011, pp. 97–104.
20.
go back to reference Ziat M, Wagner S, Frissen I. Haptic feedback to compensate for the absence of horizon cues during landing. In: International conference on human haptic sensing and touch enabled computer applications. Springer; 2016, pp. 47–54. Ziat M, Wagner S, Frissen I. Haptic feedback to compensate for the absence of horizon cues during landing. In: International conference on human haptic sensing and touch enabled computer applications. Springer; 2016, pp. 47–54.
22.
go back to reference Aaltonen I, Laarni J. Field evaluation of a wearable multimodal soldier navigation system. Appl Ergon. 2017;63:79–90.PubMedCrossRef Aaltonen I, Laarni J. Field evaluation of a wearable multimodal soldier navigation system. Appl Ergon. 2017;63:79–90.PubMedCrossRef
26.
go back to reference Deb S, Claudio D. Alarm fatigue and its influence on staff performance. IIE Trans Healthc Syst Eng. 2015;5(3):183–96.CrossRef Deb S, Claudio D. Alarm fatigue and its influence on staff performance. IIE Trans Healthc Syst Eng. 2015;5(3):183–96.CrossRef
27.
go back to reference Torabizadeh C, Yousefinya A, Zand F, Rakhshan M, Fararooei M. A nurses’ alarm fatigue questionnaire: development and psychometric properties. J Clin Monit Comput. 2017;31(6):1305–12.PubMedCrossRef Torabizadeh C, Yousefinya A, Zand F, Rakhshan M, Fararooei M. A nurses’ alarm fatigue questionnaire: development and psychometric properties. J Clin Monit Comput. 2017;31(6):1305–12.PubMedCrossRef
28.
go back to reference Petersen EM, Costanzo CL. Assessment of clinical alarms influencing nurses’ perceptions of alarm fatigue. Dimens Crit Care Nurs. 2017;36(1):36–44.PubMedCrossRef Petersen EM, Costanzo CL. Assessment of clinical alarms influencing nurses’ perceptions of alarm fatigue. Dimens Crit Care Nurs. 2017;36(1):36–44.PubMedCrossRef
29.
go back to reference McCambridge J, De Bruin M, Witton J. The effects of demand characteristics on research participant behaviours in non-laboratory settings: a systematic review. PLoS ONE. 2012;7(6):e39116.PubMedPubMedCentralCrossRef McCambridge J, De Bruin M, Witton J. The effects of demand characteristics on research participant behaviours in non-laboratory settings: a systematic review. PLoS ONE. 2012;7(6):e39116.PubMedPubMedCentralCrossRef
30.
go back to reference Lee Y-C, Lee JD, Ng Boyle L. Visual attention in driving: the effects of cognitive load and visual disruption. Hum Factors. 2007;49(4):721–33.PubMedCrossRef Lee Y-C, Lee JD, Ng Boyle L. Visual attention in driving: the effects of cognitive load and visual disruption. Hum Factors. 2007;49(4):721–33.PubMedCrossRef
31.
go back to reference Ho C, Tan HZ, Spence C. Using spatial vibrotactile cues to direct visual attention in driving scenes. Transp Res F. 2005;8(6):397–412.CrossRef Ho C, Tan HZ, Spence C. Using spatial vibrotactile cues to direct visual attention in driving scenes. Transp Res F. 2005;8(6):397–412.CrossRef
32.
go back to reference Wolpert RS. Recognition of melody, harmonic accompaniment, and instrumentation: musicians vs. nonmusicians. Music Percept Interdiscip J. 1990;8(1):95–105.CrossRef Wolpert RS. Recognition of melody, harmonic accompaniment, and instrumentation: musicians vs. nonmusicians. Music Percept Interdiscip J. 1990;8(1):95–105.CrossRef
33.
go back to reference Schellenberg EG, Habashi P. Remembering the melody and timbre, forgetting the key and tempo. Mem Cogn. 2015;43(7):1021–31.CrossRef Schellenberg EG, Habashi P. Remembering the melody and timbre, forgetting the key and tempo. Mem Cogn. 2015;43(7):1021–31.CrossRef
34.
go back to reference Siedenburg K, McAdams S. Short-term recognition of timbre sequences: music training, pitch variability, and timbral similarity. Music Percept Interdiscip J. 2018;36(1):24–39.CrossRef Siedenburg K, McAdams S. Short-term recognition of timbre sequences: music training, pitch variability, and timbral similarity. Music Percept Interdiscip J. 2018;36(1):24–39.CrossRef
38.
go back to reference Paterson E, Sanderson P, Paterson N, Loeb RG. Effectiveness of enhanced pulse oximetry sonifications for conveying oxygen saturation ranges: a laboratory comparison of five auditory displays. Br J Anaesth. 2017;119(6):1224–30.PubMedCrossRef Paterson E, Sanderson P, Paterson N, Loeb RG. Effectiveness of enhanced pulse oximetry sonifications for conveying oxygen saturation ranges: a laboratory comparison of five auditory displays. Br J Anaesth. 2017;119(6):1224–30.PubMedCrossRef
39.
go back to reference Alirezaee P, Girgis R, Kim T, Schlesinger JJ, Cooperstock JR. Did you Feel that? Developing novel multimodal alarms for high consequence clinical environments. Georgia Institute of Technology; 2017. Alirezaee P, Girgis R, Kim T, Schlesinger JJ, Cooperstock JR. Did you Feel that? Developing novel multimodal alarms for high consequence clinical environments. Georgia Institute of Technology; 2017.
40.
go back to reference Burdick K, Courtney M, Wallace MT, Baum Miller SH, Schlesinger JJ. Living and working in a multisensory world: from basic neuroscience to the hospital. Multimodal Technol Interact. 2019;3(1):2.CrossRef Burdick K, Courtney M, Wallace MT, Baum Miller SH, Schlesinger JJ. Living and working in a multisensory world: from basic neuroscience to the hospital. Multimodal Technol Interact. 2019;3(1):2.CrossRef
41.
go back to reference Eagle DM, Baunez C, Hutcheson DM, Lehmann O, Shah AP, Robbins TW. Stop-signal reaction-time task performance: role of prefrontal cortex and subthalamic nucleus. Cereb Cortex. 2007;18(1):178–88.PubMedCrossRef Eagle DM, Baunez C, Hutcheson DM, Lehmann O, Shah AP, Robbins TW. Stop-signal reaction-time task performance: role of prefrontal cortex and subthalamic nucleus. Cereb Cortex. 2007;18(1):178–88.PubMedCrossRef
43.
go back to reference Verbruggen F, Logan GD. Models of response inhibition in the stop-signal and stop-change paradigms. Neurosci Biobehav Rev. 2009;33(5):647–61.PubMedCrossRef Verbruggen F, Logan GD. Models of response inhibition in the stop-signal and stop-change paradigms. Neurosci Biobehav Rev. 2009;33(5):647–61.PubMedCrossRef
44.
go back to reference Eva KW, Link CL, Lutfey KE, McKinlay JB. Swapping horses midstream: factors related to physicians’ changing their minds about a diagnosis. Acad Med J Assoc Am Med Coll. 2010;85(7):1112.CrossRef Eva KW, Link CL, Lutfey KE, McKinlay JB. Swapping horses midstream: factors related to physicians’ changing their minds about a diagnosis. Acad Med J Assoc Am Med Coll. 2010;85(7):1112.CrossRef
45.
go back to reference Royall DR, et al. Executive control function: a review of its promise and challenges for clinical research. A report from the Committee on Research of the American Neuropsychiatric Association. J Neuropsychiatry Clin Neurosci. 2002;14(4):377–405.PubMedCrossRef Royall DR, et al. Executive control function: a review of its promise and challenges for clinical research. A report from the Committee on Research of the American Neuropsychiatric Association. J Neuropsychiatry Clin Neurosci. 2002;14(4):377–405.PubMedCrossRef
46.
go back to reference Verbruggen F, Logan GD, Stevens MA. STOP-IT: windows executable software for the stop-signal paradigm. Behav Res Methods. 2008;40(2):479–83.PubMedCrossRef Verbruggen F, Logan GD, Stevens MA. STOP-IT: windows executable software for the stop-signal paradigm. Behav Res Methods. 2008;40(2):479–83.PubMedCrossRef
47.
go back to reference Mauchly JW. Significance test for sphericity of a normal n-variate distribution. Ann Math Stat. 1940;11(2):204–9.CrossRef Mauchly JW. Significance test for sphericity of a normal n-variate distribution. Ann Math Stat. 1940;11(2):204–9.CrossRef
48.
go back to reference Ross LA, Saint-Amour D, Leavitt VM, Javitt DC, Foxe JJ. Do you see what I am saying? Exploring visual enhancement of speech comprehension in noisy environments. Cereb Cortex. 2006;17(5):1147–53.PubMedCrossRef Ross LA, Saint-Amour D, Leavitt VM, Javitt DC, Foxe JJ. Do you see what I am saying? Exploring visual enhancement of speech comprehension in noisy environments. Cereb Cortex. 2006;17(5):1147–53.PubMedCrossRef
49.
go back to reference Blum JR, Frissen I, Cooperstock JR. Improving haptic feedback on wearable devices through accelerometer measurements. In: Proceedings of the 28th annual ACM symposium on user interface software and technology. ACM; 2015, pp. 31–6. Blum JR, Frissen I, Cooperstock JR. Improving haptic feedback on wearable devices through accelerometer measurements. In: Proceedings of the 28th annual ACM symposium on user interface software and technology. ACM; 2015, pp. 31–6.
Metadata
Title
SAVIOR ICU: sonification and vibrotactile interface for the operating room and intensive care unit
Authors
Kendall J. Burdick
Seiver K. Jorgensen
Taylor N. Combs
Megan O. Holmberg
Samantha P. Kultgen
Joseph J. Schlesinger
Publication date
01-08-2020
Publisher
Springer Netherlands
Keyword
Fatigue
Published in
Journal of Clinical Monitoring and Computing / Issue 4/2020
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-019-00381-1

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