PMID- 36365939
OWN - NLM
STAT- MEDLINE
DCOM- 20221114
LR  - 20221117
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 22
IP  - 21
DP  - 2022 Oct 27
TI  - Analysis of IoT-Related Ergonomics-Based Healthcare Issues Using Analytic 
      Hierarchy Process Methodology.
LID - 10.3390/s22218232 [doi]
LID - 8232
AB  - The objective of the present work is for assessing ergonomics-based IoT (Internet 
      of Things) related healthcare issues with the use of a popular multi-criteria 
      decision-making technique named the analytic hierarchy process (AHP). Multiple 
      criteria decision making (MCDM) is a technique that combines alternative 
      performance across numerous contradicting, qualitative, and/or quantitative 
      criteria, resulting in a solution requiring a consensus. The AHP is a flexible 
      strategy for organizing and simplifying complex MCDM concerns by disassembling a 
      compound decision problem into an ordered array of relational decision components 
      (evaluation criteria, sub-criteria, and substitutions). A total of twelve 
      IoT-related ergonomics-based healthcare issues have been recognized as Lumbago 
      (lower backache), Cervicalgia (neck ache), shoulder pain; digital eye strain, 
      hearing impairment, carpal tunnel syndrome; distress, exhaustion, depression; 
      obesity, high blood pressure, hyperglycemia. "Distress" has proven itself the 
      most critical IoT-related ergonomics-based healthcare issue, followed by obesity, 
      depression, and exhaustion. These IoT-related ergonomics-based healthcare issues 
      in four categories (excruciating issues, eye-ear-nerve issues, psychosocial 
      issues, and persistent issues) have been compared and ranked. Based on calculated 
      mathematical values, "psychosocial issues" have been ranked in the first position 
      followed by "persistent issues" and "eye-ear-nerve issues". In several industrial 
      systems, the results may be of vital importance for increasing the efficiency of 
      human force, particularly a human-computer interface for prolonged hours.
FAU - Upadhyay, Hemant K
AU  - Upadhyay HK
AUID- ORCID: 0000-0002-2102-1084
AD  - BM Institute of Engineering and Technology, Sonepat 131001, India.
FAU - Juneja, Sapna
AU  - Juneja S
AUID- ORCID: 0000-0003-4601-7679
AD  - KIET Group of Institutions, Delhi NCR, Ghaziabad 201206, India.
FAU - Muhammad, Ghulam
AU  - Muhammad G
AUID- ORCID: 0000-0002-9781-3969
AD  - Department of Computer Engineering, College of Computer and Information Sciences, 
      King Saud University, Riyadh 11543, Saudi Arabia.
FAU - Nauman, Ali
AU  - Nauman A
AUID- ORCID: 0000-0002-2133-5286
AD  - Department of Information and Communication Engineering, Yeungnam University, 
      Gyeongsan 38541, Korea.
FAU - Awad, Nancy Awadallah
AU  - Awad NA
AD  - Department of Computer and Information Systems, Sadat Academy for Management 
      Sciences, Cairo 11742, Egypt.
LA  - eng
GR  - RSP-2021/34/Researchers Supporting Project number (RSP-2021/34), King Saud 
      University, Riyadh, Saudi Arabia/
PT  - Journal Article
DEP - 20221027
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
SB  - IM
MH  - Humans
MH  - *Decision Making
MH  - *Analytic Hierarchy Process
MH  - Ergonomics
MH  - Delivery of Health Care
MH  - Obesity
PMC - PMC9655769
OTO - NOTNLM
OT  - Internet of Things (IoT)
OT  - analytic hierarchy process
OT  - ergonomics
OT  - healthcare
COIS- The authors declare no conflict of interest.
EDAT- 2022/11/12 06:00
MHDA- 2022/11/15 06:00
PMCR- 2022/10/27
CRDT- 2022/11/11 01:52
PHST- 2022/09/19 00:00 [received]
PHST- 2022/10/18 00:00 [revised]
PHST- 2022/10/21 00:00 [accepted]
PHST- 2022/11/11 01:52 [entrez]
PHST- 2022/11/12 06:00 [pubmed]
PHST- 2022/11/15 06:00 [medline]
PHST- 2022/10/27 00:00 [pmc-release]
AID - s22218232 [pii]
AID - sensors-22-08232 [pii]
AID - 10.3390/s22218232 [doi]
PST - epublish
SO  - Sensors (Basel). 2022 Oct 27;22(21):8232. doi: 10.3390/s22218232.