15. Predictive Models for Estimating Metabolic and Physical Workload Based on Individual'S Recorded Heart Rate and Physical Characteristics

2004 ◽  
Author(s):  
B. Kamalakannan ◽  
A. Freivalds ◽  
W. Groves
Keyword(s):  
Heart Rate ◽  
Predictive Models ◽  
Physical Characteristics ◽  
Physical Workload

Estimating relative physical workload using heart rate monitoring: a validation by whole-body indirect calorimetry

2004 ◽  
Vol 94 (1-2) ◽  
pp. 46-53 ◽  
Author(s):  
Martin Garet ◽  
Gil Boudet ◽  
Christophe Montaurier ◽  
Michel Vermorel ◽  
Jean Coudert ◽  
...  
Keyword(s):  
Heart Rate ◽  
Indirect Calorimetry ◽  
Physical Workload ◽  
Whole Body ◽  
Heart Rate Monitoring

scholarly journals The Influence of Physical Workload Patterns and Breaks on Heart Rate Recovery

2010 ◽  
Vol 52 (1) ◽  
pp. 12
Author(s):  
Manabu KADOYA ◽  
Hiroyuki IZUMI ◽  
Makoto KUBOTA ◽  
Tsuyoshi YAMASHITA ◽  
Masaharu KUMASHIRO
Keyword(s):  
Heart Rate ◽  
Heart Rate Recovery ◽  
Physical Workload

scholarly journals Predictive factors of cardiovascular changes depending on the type and intensity of physical activity in professional athletes

2021 ◽  
Vol 26 (10) ◽  
pp. 4647
Author(s):  
N. P Garganeeva ◽  
I. F. Taminova ◽  
V. V. Kalyuzhin ◽  
E. V Kalyuzhina ◽  
I. N. Smirnova
Keyword(s):  
Physical Activity ◽  
Blood Pressure ◽  
Heart Rate ◽  
Logistic Regression ◽  
Prognostic Factors ◽  
Predictive Models ◽  
Left Ventricular ◽  
Professional Athletes ◽  
Young Athletes ◽  
Cardiovascular Changes

Aim. To determine the early predictive factors of cardiovascular changes in professional athletes, depending on the type and intensity of physical activity.Material and methods. A total of 136 male athletes were examined. Of these, 116 were professional athletes (age, 22,07±4,1 years) as follows: freestyle wrestling, judo (n=30), cross-country skiing, biathlon (n=27), powerlifting (n=33), volleyball (n=26). Control group included 20 athletes (age, 17,95±1,5 years) with a history of training less than 3 years. All participants underwent electrocardiography (ECG), echocardiography, cycle ergometry (CE) with assessment of physical performance at a heart rate of 170 bpm (PWC170) and maximum oxygen consumption (MOC). When creating predictive models of early cardiovascular changes, we used logistic regression, stepwise regression and Wald statistics. Differences were considered significant at p<0,05.Results. Predictive models of logistic regression using ROC analysis showed high sensitivity and specificity, a high percentage of correct predictions using data from echocardiography — 86,8%, CE — 80,9%, ECG and other indicators — 83,1%. A stepwise algorithm was used to select prognostic factors determining early cardiovascular changes in young athletes, depending on the stage of sports training, the intensity and type of dynamic and/or static exercise: left ventricular posterior wall thickness (p=0,008), left ventricular mass (p=0,001), stroke volume (p=0,002), end-systolic volume (p=0,001), PWC170 (p=0,025), MOC (p=0,003), recovery time of heart rate (HR) (p=0,029) and blood pressure (p=0,032) after submaximal exercise on a cycle ergometer, body mass index (p=0,029), heart rate (p=0,034), office systolic blood pressure (p=0,009), intraventricular (bundle) block (p=0,046), left ventricular repolarization abnormalities (p=0,010), mild cardiac connective tissue anomalies (p=0,035).Conclusion. The early prognostic factors established by the logistic regression affect the characteristics and risk of cardiovascular changes in each group of young athletes. This demonstrates the need to develop individual medical support programs, further monitoring, evaluation, correction and prevention of identified disorders, taking into account the type of sports, intensity and exercise.

scholarly journals Change in mental and physical workload during motorcycle riding using heart rate variability.

1999 ◽  
Vol 35 ◽  
pp. 260-261
Author(s):  
Yasufumi Mizuno ◽  
Kiyoko Yokoyama ◽  
Yoko Morimoto ◽  
Kazuyuki Takata
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Physical Workload

Assessing the Level of Physical Activity in the Workplace

2019 ◽  
Vol 11 (1) ◽  
pp. 44-56 ◽  
Author(s):  
Pedro Narváez ◽  
José Manjarrés ◽  
Winston Percybrooks ◽  
Mauricio Pardo ◽  
Maria Calle
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Body Temperature ◽  
Mobile Application ◽  
Physical Workload ◽  
Skin Response ◽  
Risk Sources ◽  
Stress Fatigue ◽  
Cardiac Cost

Occupational hygiene requires evaluation of different risk sources in the workplace. The level of physical workload may create stress, fatigue and injuries. Therefore, activity monitoring provides valuable information for companies in assessing and solving possible hazards in the workplace. The article presents a system using wearable technology to monitor and evaluate physical workload with in situ measurements. The system uses a smartwatch and a mobile application for Android phones. During workload monitoring, the application displays physiologic variables such as heart rate, calories, body temperature, galvanic skin response and number of steps. Additionally, the system computes absolute and relative cardiac cost, and Frimat coefficients. Tests were performed on 10 individuals from a janitor staff (5 men and 5 women), monitoring every task during their most demanding hour. Results agree with the type of activity developed in different intervals, showing light and very light workload for different tasks in all workers.

Effects of Familiarity of Music on Vigilant Performance

1979 ◽  
Vol 49 (1) ◽  
pp. 71-74 ◽  
Author(s):  
Craig W. Fontaine ◽  
Norman D. Schwalm
Keyword(s):  
Heart Rate ◽  
Vigilance Task ◽  
Physical Characteristics ◽  
Psychological Characteristics ◽  
Vigilance Decrement ◽  
Vigilance Performance

35 subjects, randomly assigned to five groups in a 2 × 2 + 1 between-subjects design, performed a vigilance task under familiar rock, familiar easy-listening, unfamiliar rock, unfamiliar easy-listening, and no music conditions. Familiar music significantly increased heart rate and percent detections and also mitigated the classical vigilance decrement. Type of music had no significant effect. It was concluded that the psychological characteristics of noise are at least as important as its physical characteristics in determining level of vigilance performance.

scholarly journals Redesain Metode Kerja Guna Reduksi Workload Fisik Dan Mental Pekerja Di Pt. Spu Palembang

Jurnal Tekno ◽  
2020 ◽  
Vol 17 (2) ◽  
pp. 44-58
Author(s):  
Heri Setiawan ◽  
Christofora Desi Kusmindari
Keyword(s):  
Heart Rate ◽  
Calculation Method ◽  
Mental Workload ◽  
Physical Workload ◽  
Task Load ◽  
Process Measurement ◽  
A Value ◽  
Nasa Tlx ◽  
Almost All ◽  
Industrial Company

                PT. SPU Palembang is an industrial company that produces Hospital Furniture and Rehabilitation products with the trademark SHIMA. This study aims to reduce the physical and mental workload received by workers in the Machine Shop Department. This research is focused on the production process .Measurement of physical workload uses the calculation of the worker's heart rate by calculating the percentage of Cardiovascular Load (CVL). Measurement of mental workload using the National Aeronautics and Space Administration Task Load Index (NASA-TLX) score calculation method. The results obtained based on the aspect of NASA-TLX before the proposal almost all workers receive a mental workload with a value of > 80 that is included in the category of heavy mental workloads except Milling-Drilling Workers (4) have a score < 80 in the category of moderate mental workload. After the proposal all workers have a score < 80 so that the mental workload received falls into the medium category. Based on the proposals applied to the Lathe Worker (1) and the Milling-Drilling Worker (4) namely the improvement of work methods in the process of turning, punching, and the proposed holding of a reminder as a tool to remember, the results obtained %CVL from both workers < 30%. Three other workers, although experiencing a decline, remained at > 30%. The category of mental workload received by workers from previously included in the category of heavy mental workload dropped to moderate

scholarly journals Evaluation of Mental and Physical Workload while Driving using Wavelet Transform of Heart Rate Time Series

2002 ◽  
Vol 122 (1) ◽  
pp. 36-41 ◽  
Author(s):  
Kiyoko Yokoyama ◽  
Naofumi Omi ◽  
Yoko Morimoto ◽  
Yasufumi Mizuno ◽  
Kazuyuki Takata
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Wavelet Transform ◽  
Physical Workload

scholarly journals Cardiorespiratory and Thermoregulatory Parameters Are Good Surrogates for Measuring Physical Fatigue during a Simulated Construction Task

2020 ◽  
Vol 17 (15) ◽  
pp. 5418
Author(s):  
Shahnawaz Anwer ◽  
Heng Li ◽  
Maxwell Fordjour Antwi-Afari ◽  
Waleed Umer ◽  
Arnold Y. L. Wong
Keyword(s):  
Heart Rate ◽  
Skin Temperature ◽  
Electrodermal Activity ◽  
Physical Workload ◽  
Breathing Rate ◽  
Physical Fatigue ◽  
Local Skin ◽  
Local Skin Temperature ◽  
The Right ◽  
Construction Task

Cardiorespiratory (e.g., heart rate and breathing rate) and thermoregulatory (e.g., local skin temperature and electrodermal activity) responses are controlled by the sympathetic nervous system. To cope with increased physical workload, the sympathetic system upregulates its activity to generate greater sympathetic responses (i.e., increased heart rate and respiratory rate). Therefore, physiological measures may have the potential to evaluate changes in physical condition (including fatigue) during functional tasks. This study aimed to quantify physical fatigue using wearable cardiorespiratory and thermoregulatory sensors during a simulated construction task. Twenty-five healthy individuals (mean age, 31.8 ± 1.8 years) were recruited. Participants were instructed to perform 30 min of a simulated manual material handling task in a laboratory. The experimental setup comprised a station A, a 10-metre walking platform, and a station B. Each participant was asked to pick up a 15 kg ergonomically-designed wooden box from station A and then carried it along the platform and dropped it at station B. The task was repeated from B to A and then A to B until the participants perceived a fatigue level > 15 out of 20 on the Borg-20 scale. Heart rate, breathing rate, local skin temperature, and electrodermal activity at the wrist were measured by wearable sensors and the perceived physical fatigue was assessed using the Borg-20 scale at baseline, 15 min, and 30 min from the baseline. There were significant increases in the heart rate (mean changes: 50 ± 13.3 beats/min), breathing rate (mean changes: 9.8 ± 4.1 breaths), local skin temperature (mean changes: 3.4 ± 1.9 °C), electrodermal activity at the right wrist (mean changes: 7.1 ± 3.8 µS/cm), and subjective physical fatigue (mean changes: 8.8 ± 0.6 levels) at the end of the simulated construction task (p < 0.05). Heart rate and breathing rate at 15 and 30 min were significantly correlated with the corresponding subjective Borg scores (p < 0.01). Local skin temperature at 30 min was significantly correlated with the corresponding Borg scores (p < 0.05). However, electrodermal activity at the right wrist was not associated with Borg scores at any time points. The results implied cardiorespiratory parameters and local skin temperature were good surrogates for measuring physical fatigue. Conversely, electrodermal activity at the right wrist was unrelated to physical fatigue. Future field studies should investigate the sensitivity of various cardiorespiratory and thermoregulatory parameters for real time physical fatigue monitoring in construction sites.

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