EXPERIMENTAL MACHINE LEARNING OF FINGER PHOTOPLETHYSMOGRAPHY (PPG) FOR AUTONOMOUS HOSPITAL BED PUSHING FRAMEWORK USING POLYNOMIAL REGRESSION
Keywords:Machine Learning, Polynomial Regression, Photoplethysmography, Autonomous Hospital Bed Pushing, Vitals Monitoring, Nursing
In community-based healthcare, the nursing workforce requires low-skilled nursing automation in the hospital to accelerate talent development towards high-skilled advance practice nurse for community deployment. As precursor, the hospital bed pushing operation for medium-risk patient was hypothesized as a novice nursing task where artificial intelligence automation is possible. The solution framework was embodied by a concept of operation with non-invasive vitals monitoring as priority to study feasibility in addressing patient life-safety requirements. Polynomial regression machine learning of 65 one-hour sets of finger PPG data from a single subject were collected and studied. Convergence of finger PPG to 8th degree polynomial was observed which suggested process feasibility towards establishing patient safe states during autonomous journey. Process reliability ranged between 2% to 95% with long PPG counts as influencing factor for drops in reliability score. Motivation/Background: A predictable non-invasive vitals monitoring was priority to enable autonomous hospital bed pushing framework to address patient life-safety concerns during autonomous journey. Finger PPG is a non-invasive and easy to use method to monitor heart related activities and used to study for convergence and reliability within the framework. Method:65 one-hour sets of finger PPG was recorded from a single male, age 27 subject. The data was processed by polynomial regression machine learning technique to output the degree of polynomial with highest cross validation score mean. Results: Convergence of regressed PPG data to 8th degree for both pre-journey and journey datasets and degree of polynomial matching reliability of 2% to 95% were observed. Conclusions: Convergence of PPG data facilitates the establishment of safe physical states in vitals monitoring, enabling the autonomous hospital bed pushing framework for further development. Reliability remains an area for improvement via medical grade.
Ministry of Health and Workforce Singapore, "Healthcare Manpower Plan 2020: Caring for the nation transforming tomorrow's healthcare," Ministry of Health2016, Available: https://www.moh.gov.sg/content/moh_web/home/pressRoom/highlights/2016/2020-healthcaremanpower-plan.html.
H. L. Dreyfus, S. E. Dreyfus, and T. Athanasiou, Mind over machine: the power of human intuition and expertise in the era of the computer. The Free Press, 1986, p. 231.
H. L. Dreyfus and S. E. Dreyfus, "Beyond expertise: Some preliminary thoughts on mastery," A qualitative stance: Essays in honor of Steinar Kvale, pp. 113-124, 2008.
S. E. Dreyfus and H. L. Dreyfus, "A five-stage model of the mental activities involved in directed skill acquisition," California Univ Berkeley Operations Research Center1980. DOI: https://doi.org/10.21236/ADA084551
P. E. Benner, From Novice to Expert: Excellence and Power in Clinical Nursing Practice (no. v. 100). Addison-Wesley Publishing Company, Nursing Division, 1984. DOI: https://doi.org/10.1097/00000446-198412000-00025
N. Daniell, S. Merrett, and G. Paul, "Effectiveness of powered hospital bed movers for reducing physiological strain and back muscle activation," Applied Ergonomics, Article vol. 45, no. 4, pp. 849-856, 2014. DOI: https://doi.org/10.1016/j.apergo.2013.11.001
Z. Guo, R. B. Yee, K. R. Mun, and H. Yu, "Experimental evaluation of a novel robotic hospital bed mover with omni-directional mobility," Applied Ergonomics, Article vol. 65, pp. 389-397, 2017. DOI: https://doi.org/10.1016/j.apergo.2017.04.010
C. Wang, A. S. Matveev, A. V. Savkin, R. Clout, and H. T. Nguyen, "A semi-autonomous motorized mobile hospital bed for safe transportation of head injury patients in dynamic hospital environments without bed switching," Robotica, Article vol. 34, no. 8, pp. 1880-1897, 2016.
J. A. Rixe, J. H. Liu, H. A. Breaud, K. P. Nelson, P. M. Mitchell, and J. A. Feldman, "Is hallway care dangerous? An observational study," (in English), American Journal of Emergency Medicine, Article vol. 36, no. 8, pp. 1451-1454, 2018.
S. Jokic, V. Delic, Z. Peric, D. Sakac, and S. Krco, "Efficient ECG modeling using polynomial functions," (in English), Elektronika ir Elektrotechnika, Article no. 4, pp. 121-124, 2011. DOI: https://doi.org/10.5755/j01.eee.110.4.304
How to Cite
License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- The work described has not been formally published before, except in the form of an abstract or as part of a published lecture, review, thesis, or overlay journal.
- That it is not under consideration for publication elsewhere.
- That its release has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
Authors who publish with International Journal of Engineering Technologies and Management Research agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors can enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or edit it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) before and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
For More info, please visit CopyRight Section