Applicability of Physiological Monitoring Systems within Occupational Groups: A Systematic Review
Abstract
:1. Introduction
2. Methods
3. Results
3.1. Studies Selection
3.2. Characteristics of the Included Studies
3.3. Risk of Bias Assessment and Quality of Results
4. Discussion
4.1. Monitored Physiological Variables
4.1.1. Cardiac and Thermal Responses
4.1.2. Other Monitored Variables
4.2. Physiological Monitoring Systems and Processing Methods
4.3. Safety and Health Applications
4.3.1. Thermal Stress
4.3.2. Physiological Workload
4.3.3. Stress Detection
4.3.4. Physical Activity Patterns
4.3.5. Cardiac Activity
4.3.6. Fatigue
4.4. Current Trends and Future Research Perspectives
4.5. Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Signals Acquired | Physiological Monitoring Systems | System Specifications/Key Features | Reported Measurement Characteristics | Number of Studies | References |
---|---|---|---|---|---|
Cardiac only | Polar heart rate monitors (Polar Electro, Kemple, Finland): Team Pro, H7, S625X, RCX3, Vantage XL, S710 |
| Not reported | 8 | [40,49,65,67,68,70,71,72] |
H12+ digital Holter recorder V3.12 (Mortara Instrument, Milwaukee, Brookfield, WI, USA) |
| Not reported | 3 | [41,64,72] | |
Garmin Smartwatch (Garmin International, Olathe, KS): Forerunner 110 monitor and Vivoactive HR |
| Not reported | 3 | [46,58,61] | |
Apple Watch Series 1 |
| Not reported | 1 | [55] | |
Heart rate sensor myBeat WHS-2 (Union Tool Co., Ltd., Shanghai, China) |
| 5-min interval | 1 | [48] | |
Respiratory only | Open-circuit spirometry system (K4b2, Cosmed Srl, Rome, Italy) |
| Not reported | 4 | [66,67,68,73] |
AeroSport KB1-C ambulatory metabolic analysis, open-circuit spirometry-based system (AeroSport, Inc., Ann Arbor, MI, USA) |
| 20-s measurement interval | 1 | [71] | |
Multivariable signals | Integrated monitor Equivital Life Monitor EQ-01 and EQ-02 (Hidalgo, Cambridge, UK) |
| Not reported | 7 | [42,51,57,63,69,73,77] |
Chest-strap Zephyr status monitor |
| Not reported | 4 | [45,53,56,59] | |
Biofeedback 2000 x-pert system |
| EEG, EMG and respiration modules used, 13 data sections with 15 min interval | 1 | [47] | |
Wristband-type biosensor E4 manufactured by Empatica, Cambridge, Massachusetts |
| PPG: sampling rate of 64 Hz and an output resolution of 09 nW/digit. EDA: 4-Hz sampling frequency, 900-pS resolution, and range of 0.01–10 μS. Infrared thermopile: sampling rate of 4 Hz and accuracy of 0.02 °C within normal skin temperature | 2 | [50,76] | |
Chest-worn sensor EcgMove 3 (Movisens) |
| Not reported | 2 | [54,60] | |
Smart clothing COCOMI (TOYOBO Co., Ltd., Osaka city, Japan) (heart rate, respiration, perspiration, body surface temperature and joint angle) |
| Not reported | 1 | [48] | |
Samsung Galaxy S4 (Android 4.2.2 Jelly Bean Operation System, octa-core chipset, 1.6-GHz Quad + 1.2 GHz Quad CPU) |
| 1 | [59] | ||
Basis Fitness Wristband: B1 and Basis Peak™ (BASIS, an Intel Company, San Francisco, CA, USA) |
| 1-min interval | 2 | [49,59] | |
Activity sensor only | Promove 3D activity sensor (Inertia Technology, Enschede, The Netherlands) |
| Samples of accelerations in three dimensions at 40 Hz and average sum of the Integral of the Modulus of Accelerations (IMA) per minute | 1 | [43] |
LSM9DS0 sensors by STMicroelectronics, a wearable microcontroller, the Adafruit Flora, via I2C |
| Not reported | 1 | [44] | |
Wrist actigraph (Ambulatory Monitoring, Inc., Ardsley, NY, USA) |
| 1-min epochs | 1 | [52] | |
ActiGraph GT9X and wGT3X-BT (ActiGraph, LLC, Pensacola, FL, USA) |
| 100 Hz | 3 | [53,62,73] | |
Accelerometer-based wrist-worn activity tracker Fitbit Flex and Fitbit Charge 2 (Fitbit Inc., San Francisco, CA, USA) |
| Not reported | 3 | [70,74,75] | |
GeneActiv accelerometer wristband |
| Not reported | 1 | [59] | |
Philips Actiwatch Spectrum Pro |
| Not reported | 1 | [74] | |
Core temperature only | Ingestible thermometric pill (Jonah VitalSense, Respironics, Bend, OR, USA) |
| Not reported | 3 | [51,65,73] |
Appendix B
Study Reference | Risk of Bias Assessment Criteria | Score: | ||||||
---|---|---|---|---|---|---|---|---|
Study Design | Participants | Data Sources | Reporting Bias | Limitations | Generalisability | Potential Sources of Bias | ||
[40] | 0.86 | 0.60 | 1.00 | 0.83 | 0.00 | 0.00 | 1.00 | 0.61 |
[41] | 0.86 | 0.80 | 1.00 | 0.83 | 0.00 | 1.00 | 1.00 | 0.78 |
[42] | 0.86 | 0.80 | 0.50 | 1.00 | 0.00 | 1.00 | 1.00 | 0.74 |
[43] | 0.86 | 0.60 | 0.50 | 1.00 | 1.00 | 1.00 | 1.00 | 0.85 |
[44] | 0.86 | 0.40 | 0.50 | 0.83 | 0.00 | 1.00 | 1.00 | 0.66 |
[45] | 0.86 | 0.40 | 0.50 | 1.00 | 1.00 | 1.00 | 1.00 | 0.82 |
[46] | 0.86 | 0.40 | 0.50 | 1.00 | 1.00 | 1.00 | 1.00 | 0.82 |
[47] | 0.86 | 0.40 | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.75 |
[48] | 0.86 | 0.40 | 0.50 | 1.00 | 1.00 | 1.00 | 1.00 | 0.82 |
[49] | 0.86 | 0.40 | 0.50 | 1.00 | 0.00 | 1.00 | 0.33 | 0.58 |
[50] | 0.86 | 0.20 | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.72 |
[51] | 0.86 | 0.60 | 0.50 | 1.00 | 1.00 | 1.00 | 1.00 | 0.85 |
[52] | 0.86 | 0.60 | 0.50 | 1.00 | 1.00 | 1.00 | 1.00 | 0.85 |
[53] | 0.86 | 0.40 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.89 |
[54] | 0.86 | 0.60 | 0.50 | 1.00 | 1.00 | 1.00 | 1.00 | 0.85 |
[55] | 0.86 | 0.40 | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.75 |
[56] | 0.86 | 0.40 | 0.50 | 0.83 | 1.00 | 1.00 | 1.00 | 0.80 |
[57] | 0.86 | 0.40 | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.75 |
[58] | 0.86 | 0.60 | 0.50 | 1.00 | 1.00 | 1.00 | 1.00 | 0.85 |
[59] | 0.86 | 0.60 | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.78 |
[60] | 0.86 | 0.60 | 0.50 | 1.00 | 1.00 | 1.00 | 1.00 | 0.85 |
[61] | 0.86 | 0.60 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.92 |
[62] | 0.86 | 0.60 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.92 |
[77] | 0.86 | 0.40 | 0.50 | 1.00 | 1.00 | 1.00 | 1.00 | 0.82 |
[63] | 0.86 | 0.60 | 0.50 | 1.00 | 0.00 | 1.00 | 1.00 | 0.71 |
[64] | 0.86 | 0.40 | 0.50 | 0.83 | 1.00 | 1.00 | 1.00 | 0.80 |
[65] | 0.86 | 0.20 | 1.00 | 1.00 | 1.00 | 0.00 | 1.00 | 0.72 |
[66] | 0.86 | 0.20 | 0.50 | 0.67 | 1.00 | 1.00 | 1.00 | 0.75 |
[67] | 0.86 | 0.60 | 0.50 | 0.83 | 0.00 | 0.00 | 1.00 | 0.54 |
[68] | 0.86 | 0.60 | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.78 |
[69] | 0.86 | 0.60 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.92 |
[70] | 0.86 | 0.60 | 1.00 | 0.83 | 1.00 | 1.00 | 1.00 | 0.90 |
[71] | 0.71 | 0.40 | 1.00 | 1.00 | 0.00 | 1.00 | 1.00 | 0.73 |
[72] | 0.86 | 0.60 | 0.50 | 1.00 | 0.00 | 1.00 | 1.00 | 0.71 |
[73] | 0.86 | 0.60 | 0.50 | 1.00 | 0.00 | 1.00 | 1.00 | 0.71 |
[74] | 0.86 | 0.40 | 1.00 | 1.00 | 1.00 | 1.00 | 0.57 | 0.83 |
[75] | 0.86 | 0.60 | 1.00 | 1.00 | 1.00 | 1.00 | 0.71 | 0.88 |
[76] | 0.86 | 0.20 | 1.00 | 1.00 | 1.00 | 1.00 | 0.43 | 0.78 |
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Database | Adapted Query and Database Filters |
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Scopus | ((TITLE-ABS-KEY(“physiolog* monitor*”) OR TITLE-ABS-KEY(“noninvasive monitor*”) OR TITLE-ABS-KEY(“medical monitor*”) OR TITLE-ABS-KEY (“wearable sens*”)) AND (TITLE(assessment) OR TITLE-ABS-KEY(occupational) OR TITLE(model) OR TITLE-ABS-KEY(fatigue) OR TITLE(algorithm) OR TITLE-ABS-KEY(worker) OR TITLE-ABS-KEY(training) OR TITLE-ABS-KEY(“physical exertion”))) 2014–2022/Article, Article in Press/Journals/English |
PubMed | ((“physiological monitoring”[All Fields]) OR (“noninvasive monitoring”[All Fields]) OR (“wearable sensor”[All Fields]) OR (“medical monitoring”[All Fields])) AND ((assessment[Title]) OR (occupational[All Fields]) OR (model[Title]) OR (“fatigue”[All Fields]) OR (algorithm[Title]) OR (worker[All Fields]) OR (“training”[All Fields]) OR (“training”[All Fields]) OR (“physical exertion”[All Fields])) 2014–2021/Journal Article/English/Humans |
Science Direct | (“physiological monitoring” OR “noninvasive monitoring” OR “wearable sensors”) AND (TITLE(assessment) OR occupational OR TITLE(model) OR fatigue OR TITLE(algorithm) OR worker) 2014–2022/Research articles/Subscribed journals |
Web of Science | (TS = (“physiolog* monitor*”) OR TS = (“noninvasive monitor*”) OR TS = (“wearable sens*”) OR TS = (“medical monitor*”)) AND (TI = (assessment) OR TS = (occupational) OR TI = (model) OR TS = (fatigue) OR TI = (algorithm) OR TS = (worker) OR TS = (training) OR TS = (“physical exertion”)) 2014–2022/Article/English |
Academic Search Complete | (AB “physiolog* monitor*” OR AB “noninvasive monitor*” OR AB “wearable sens*” OR AB “medical monitor*”) AND (TI assessment OR AB occupational OR TI model OR AB fatigue OR TI algorithm OR AB worker OR AB training OR AB “physical exertion”) 2014–2021/Academic journals/English |
Research Objective | Occupational Groups | Physiological Variables | Secondary Variables | References | |||
---|---|---|---|---|---|---|---|
Continuously Measured (Main Variables) | Uncontinuously Measured | Biochemical | Subjective and Cognitive | Environmental | |||
Cardiovascular activity | Construction workers | HR | N/A | N/A | N/A | N/A | [49] |
Firefighters | HR, HRV, ECG | N/A | N/A | N/A | N/A | [41,64] | |
Retail store employees | HR, HRV | N/A | N/A | N/A | N/A | [55] | |
Fatigue | Operators from drillship | HR, accelerometer counts | N/A | N/A | Fatigue subjective scales | N/A | [57] |
Professional long-distance bus drivers | EEG, EMG, respiration signals | N/A | N/A | Self-reported fatigue states | N/A | [47] | |
Nurses | From accelerometry counts: sleep duration, number of awakenings and sleep latency at night; number and distribution of steps taken during the work shift | N/A | N/A | Fatigue levels using the Brief Fatigue Inventory | N/A | [74] | |
Heat stress | Bakers | HR | Tympanic body temperature | N/A | N/A | Natural wet temperature Tnw and globe temperature Tg | [40] |
Construction workers | HR, energy expenditure, oxygen consumption, physical work activity, fluid intake | Resting blood pressure | Pre- and post-shift urine specific gravity (USG) | RPE | Dry-bulb temperature, wet bulb temperature, globe temperature, Indoor and outdoor heat exposures (WBGT) | [66,67,70] | |
Custodial staff | HR, physical activity patterns from accelerometer counts | N/A | N/A | N/A | Ambient temperature and humidity | [59] | |
Farmworkers | BR, HR, skin temperature, core body temperature (estimated from skin temperature), kilocalories burned per hour | Baseline blood pressure | Serum glucose and serum osmolarity | Heat-related illness symptoms | WBGT | [45] | |
Grounds management workers | HR, activity patterns | N/A | N/A | N/A | Individually experienced temperature | [61] | |
Law enforcement personnel | HR, core temperature (estimated), physiological strain index | N/A | N/A | Self-reported thermal discomfort | N/A | [63] | |
Mine rescue workers | HR, BR, energy expenditure, oxygen consumption, core temperature and skin temperature | N/A | N/A | N/A | Mining environmental conditions | [51] | |
Rebar workers | HR, energy expenditure, BR, METs, minute ventilation, oxygen consumption, and respiratory exchange ratio | Ear temperature | N/A | RPE | N/A | [68] | |
Physiological demands and workload | Construction workers | ECG (smart clothing), HR, electrodermal activity, photoplethysmogram (PPG), skin temperature, 3-axis acceleration, oxygen consumption | N/A | N/A | N/A | Air temperature, relative humidity, WBGT | [48,71,76] |
Firefighters | HR, air consumption, core temperature, activity-based accelerometry counts, maximum oxygen uptake, ECG, speed and elevation gain | N/A | Complete blood count and differential cell count; electrolyte, muscle and liver enzymes; blood glucose, creatinine, partial thromboplastin and urine osmolarity | Body part discomfort, self-perceived conditions, RPE, perception of respiratory distress, thermal Sensation Scale, overall wellbeing (feeling scale) | N/A | [46,65,72,73,77] | |
Grounds maintenance crew workers | HR | N/A | N/A | N/A | Ambient temperature, ultraviolet exposure | [58] | |
Recruits from Marine training course | HR, activity-based accelerometry counts, and skin temperature measurements | N/A | N/A | Vigilance and memory evaluations | N/A | [42] | |
Roofers | HR, HRV, activity through accelerometry data, energy expenditure, metabolic equivalents (METs), sleep quality | N/A | N/A | Self-reported productivity loss | N/A | [53] | |
Physiological responses and Stress levels | Construction workers | cardiac reactivity (HR, IBI, HRV, HRR), electrodermal level and response (from skin temperature) | N/A | Cortisol levels in saliva | N/A | N/A | [50] |
Firefighters | HR, activity based on tri-axial acceleration counts, skin temperature, BR | N/A | N/A | Self-assessed stress | N/A | [69] | |
Office workers | Cardiac reactivity, physical activity, sleep quality | N/A | N/A | Perceived stress | Relative humidity | [54,60] | |
Police officers | HR, HRV, BR | N/A | N/A | Self-reported stress | N/A | [56] | |
Physical activity patterns assessment | Nurses | Activity, posture and sleep patterns from acceleration counts, circadian rhythm parameters and sleep quantity; angular displacement waveforms of upper arm elevation and trunk flexion/extension; HR | N/A | N/A | Emotional and physical wellbeing; behavioural variables (sleep quality, affect, anxiety, life satisfaction, personality) | N/A | [44,52,62,75] |
Office workers | Activity based on accelerometer counts | N/A | N/A | N/A | N/A | [43] |
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Bustos, D.; Guedes, J.C.; Baptista, J.S.; Vaz, M.P.; Costa, J.T.; Fernandes, R.J. Applicability of Physiological Monitoring Systems within Occupational Groups: A Systematic Review. Sensors 2021, 21, 7249. https://doi.org/10.3390/s21217249
Bustos D, Guedes JC, Baptista JS, Vaz MP, Costa JT, Fernandes RJ. Applicability of Physiological Monitoring Systems within Occupational Groups: A Systematic Review. Sensors. 2021; 21(21):7249. https://doi.org/10.3390/s21217249
Chicago/Turabian StyleBustos, Denisse, Joana C. Guedes, João Santos Baptista, Mário P. Vaz, José Torres Costa, and Ricardo J. Fernandes. 2021. "Applicability of Physiological Monitoring Systems within Occupational Groups: A Systematic Review" Sensors 21, no. 21: 7249. https://doi.org/10.3390/s21217249
APA StyleBustos, D., Guedes, J. C., Baptista, J. S., Vaz, M. P., Costa, J. T., & Fernandes, R. J. (2021). Applicability of Physiological Monitoring Systems within Occupational Groups: A Systematic Review. Sensors, 21(21), 7249. https://doi.org/10.3390/s21217249