Mikhail Kolesnikov, ITMO University, St. Petersburg, Russia, email@example.com
Maxim Afanasev, ITMO University, St. Petersburg, Russia, firstname.lastname@example.org
Yuri Andreev, ITMO University, St. Petersburg, Russia, email@example.com
Yuri Fedosov, ITMO University, St. Petersburg, Russia, firstname.lastname@example.org
Kseniia Zimenko, ITMO University, St. Petersburg, Russia, zksenia itmo.ru
Anastasiya Krylova, ITMO University, St. Petersburg, Russia, email@example.com
Sergey Shorokhov, ITMO University, St. Petersburg, Russia, firstname.lastname@example.org
Abstract — This paper states a description of the principles of measuring and increasing labor productivity using modern technologies and the author’s concept of the socio-cyberphysical system named Smart Ergonomics and its technical implementation of decision making system Smart Ergonomics Management System (SEMS). The essence of this technology is the implementation of flexible planning of all processes of an employee’s work time by dynamically adjusting the environment and applying individual methods of influencing an employee’s physical and psychological condition, as well as maintaining employee’s productive and relaxation phases and ensuring smooth transitions between them, using the collected in real-time data. As a result of the work, impact methods and information sources are analyzed and classified, the technologies used for collecting, storing and processing data, as well as the environment changing actors are described.
Keywords: socio-cyber-physical system, workforce productivity, human capital, sustainable lifestyle, health, automation, internet of things
© The Authors, published by CULTURAL-EDUCATIONAL CENTER, LLC, 2020
This work is licensed under Attribution-NonCommercial 4.0 International
With the introduction of the concept of Industry 4.0, a significant increase in the number of automation and robotics technologies in production processes are observed. Therefore a person is occupying a significantly smaller part in manufacturing processes that require low qualifications. Thus, the activity of a modern person in enterprises becoming more valuable in higher-level tasks, such as management, design and programming , .
In order to be able to cope with high-level tasks, a significant contribution to improving labor’s human potential is required.
In modern society there is a wide range of disorders that impede the growth of productivity of employees and students associated with low working conditions and the level of quality of life .
The list of such problems includes: High morbidity, depression, overwork, burnout, increasing level of procrastination, lack of physical activity, insomnia, inattention — and many other ailments inherent in a large part of the working population. At the moment, there are a number of scientific methods for optimizing the workflow, such as Human Resource Management, Human Factors and Ergonomics — that cover the context of describing employee relationships, rules for working with equipment and completing tasks, organizing space. However, implementation of this knowledge at the moment remains static and non-individual.
On the other hand, there is a huge amount of scientific work on the application of Internet of Things, Big Data and Machine Learning technologies in enterprises in order to optimize daily processes available. One example of the application of such a set of technologies is the organization of advanced flexible production, i. e. production capable of dynamically adapting to the changing tasks in real-time in order to ensure maximum production speed and maximum product quality under conditions of the need for its high individualization while maintaining the principles of lean production.
As a result of combining the technologies and knowledge of the above concepts, a new concept of a socio-cyber-physical system arises, the essence of which is to carry out flexible planning of the employee’s workflow, provide a dynamically adaptable environment and effective application of impact methods for an individual that influence his physical and psychological state in order to maintain phases of activity or rest of the employee and ensure smooth and consciously planned transitions between them. In terms of this work described author’s concept is called Smart Ergonomics. It’s technical implementation in the form of a management system is called Smart Ergonomics Management System (SEMS).
This paper highlights the key advantages of the flexible concept of Smart Ergonomics comparing to the classic methods for increasing workforce productivity. In the related work section a detailed analyze of the main impact methods and information sources and their classification is provided. A research method and experiment details as well as planned results are covered in the research methods section. A list of possible features regarding future development of Smart Ergonomics concept and integration of SEMS to other key human activities is described in discussion section.
II. Related Work
The concept of Smart Ergonomics and associated scientific work on increasing the productivity and overall human potential growth may find their use in almost all areas of human activity. The system can find the most relevant application in the optimization of labor and the educational process as well as in medicine, security and marketing. It is also worth mentioning that the potential economic benefits from the use of SEMS in enterprises would be obtained. As a result of improving staff efficiency a reduce the incidence rate of employees and increase of the prestige of the company in the context of conscious care for employees can be achieved .
Currently there are no relevant scientific works available regarding the idea of improving labor productivity using collected health data and adjusting the environment, combining the overview of information sources and impact methods. In terms of this work, a classification of information sources and impact methods was formed in order to obtain a clear vision of relevant parameters and effective scenarios.
A. Impact Methods
As a result of the analysis of the currently available methods of influencing a person at the workplace or in educational institutions, two main classes of methods were formed that differ in duration and the possibility of dynamic dosing — passive and active. An additional class was introduced to the classification of methods for exerting a positive effect on productivity — the static class, which reflects general working conditions to ensure maximum productivity, which do not require significant individualization or changes over time .
Static impact methods provide the minimum necessary characteristics of working conditions, which may not change over time and be maintained at the enterprise universally for all employees, individual groups, or individually. This class of methods includes the influence of the following parameters:
1) Air quality.
2) CO2 level should be at 250–400 ppm. Higher ppm level cause sleepiness and distractions :
a) Negative air ionization solves some of the seasonal disorders ;
b) Decrease of particulate matter (PM2.5, PM10) level. This remains an important factor of air quality and significantly affect productivity ;
c) Decrease of total volatile organic compounds (TVOC) level. TVOC are one of the hazardous air pollutants that can have negative effect on health in the long run;
d) Maintaining humidity level of 35–42.5. Air humidity have an effect on overall health and comfort of labor since it affects skin humidity and respiratory cooling% .
3) Lighting :
a) Improvement of color rendering index (CRI). Optimal value is 90 and higher;
b) Maintaining the required lighting intensity. Recommended indoor light level is 500lx. Optimal light intensity on the working surface should stay in range of 150–250lx.
4) Reduce of noise Pollution . This is also versy important pollutant that may cause hearing impairment, tinnitus, hypertension, ischemic heart disease, annoyance, sleep disturbance and other disorders. Optimal sound level for office workers should remain less than 35dBA. The most common noise pollutants are: outside environmental noises, car traffic, equipment, ventilation systems, people conversation etc.
5) Sleep quality , :
a) Optimal total sleep duration is 7–9 hours;
b) Deep sleep phase duration takes at least 20% of total sleep time;
c) Exclusion of indoor lighting sources from household appliances or other devices;
d) Electromagnetic pollution reduction may be achieved by turning off all the wireless devices;
e) Elimination of background noise pollution.
6) Nutrition .
Passive methods mean discrete methods with a long-lasting effect, the application of which can be carried out in relation to an employee outside of the work process, i. e. during rest or preparation for work:
1) Pharmaceuticals with both soothing or stimulating effect;
2) Sensory deprivation can help relieve stress and anxiety ;
3) Physical activity is an important part of workflow and can help keeping body and mind active. Physical activity also prevents passive lifestyle ;
4) Games and puzzles are a great tools to support cooperative and competitive spirit in team and stimulate brain activity ;
5) Social activity is an important aspect in any type of jobs. Lack of social activity cause lower productivity and negatively affect overall well-being of labor;
6) Interaction with nature have similar effect with social interaction as one of our natural needs;
7) Aromatherapy (alt. medicine) has a relaxing effect on some of groups of people with help of essential oils .
Active methods are understood as methods of influencing the physical and psychological state of an employee in the process of work through dynamic dosing:
1) Light and color , , , . At the moment this factor remains one of the most studied and has more scientific proves than others. It is proved that changing lighting can have effect on productivity of labor by stimulating brain activity and running internal biological processes associated with human biorhythms:
a) Light intensity,
b) Lighting temperature,
c) Light therapy, color therapy.
2) Air parameters:
a)Air oxygen concentration. Changing this parameter impacts the amount of oxygen lungs receive and deliver to cardiovascular system. Low blood oxygen level leads to tiredness, early fatigue and confusion. Higher levels can cause relaxing effect;
b) Temperature . Changing this parameter creates more or less comfortable conditions and can lead to stimulating labor of making environment more relaxing. Constantly elevated temperatures cause lower productivity;
c) Air flows has a cooling effect and can help maintaining the productivity at needed level by using similar effect with air temperature;
d) Atmospheric pressure. By changing this parameter cardiovascular stress can be regulated. Some of the physical exercises can be simulated.
3) Fragrance , . Smell remains one of the most important impact methods and can have significant relaxing or stimulating effect. This can be achieve using different fragrance sources:
a) Aromatic substances,
b) Essential oils,
c) Natural odors.
4) Sounds and music. Hearing is another important information channel for our body. It is proven that providing different types of sounds and music has a powerful relaxation or stimulating effect:
b) Environmental sounds ;
c) Various sound frequencies ;
d) Autonomous sensory meridional reaction (ASMR) , .
5) Kinesthetics. This type of impact methods can be used as a complement to the listed above:
a) Massage ;
b) Electrical stimulation;
d) Body positioning.
6) Injection and intravenous infusion. Can have a very powerful and long-lasting effect. However, more scientific research should be involved.
B. Information Sources
In addition to well-known information sources, including works devoted to the multifaceted study of the human body and its interaction with the outside world, which allow us to determine in advance universal favorable working conditions, there are also methods for collecting real-time data on the human condition, which can be used for statistical analysis and proactive decision-making, as well as for making decisions regarding the working day and the employee’s environmental conditions in real time.
In the process of analyzing the currently available methods of measuring the parameters of the human body in order to determine the physical state, three main classes of information sources were formed, which differ in the agility of the parameter’s change, duration and frequency of its measurement. In this work information sources were classified on this classes: static, passive and active. An additional class was added to this classification — autonomous.
The static class allows taking into account scientific knowledge in the field of determining universally optimal working conditions, when both passive and active sources allow you to get more accurate and relevant information about the employee and form automation of the work plan within a week, day, or even every minute. However, special attention should be paid to an autonomous active class of information sources, which allows to dynamically and objectively assess the state of an employee not only within a working day.
Static class of information sources includes scientific knowledge about a person, it’s biological rhythms, as well as optimal working conditions universal for the body. The list of sources of information for this class includes the following aspects:
1) HR management;
2) Labor protection and principles of the Scientific Organization of Labor;
a) Circadian rhythms;
b) The immune system.
5) The specifics of the enterprise;
6) Specific employee information.
a) Skills and hobbies:
c) b) Health, physical well-being and contraindications;
d) c) Social status, marital status;
e) d) Financial position and overall quality of life.
Passive sources of information allow you to obtain information about an employee iterative, i. e. before work, in the process of work, between the various stages of performing work and when changing phases of work and rest, and also at the end of the working day. Also in this class of sources includes slowly changing environmental conditions that are able to maintain their effect within the framework of the working day. The use of these sources allows you to create a more detailed statistical profile of the employee and prepare optimal individual working conditions.
a) Physical condition;
b) Psychological state;
2) Assessment of the recent events.
3) Health Assessment:
a) Keeping a medical record;
b) Disease Symptoms Tracking.
4) Assessment of sleep quality;
5) Environmental conditions:
a) Weather, atmospheric pressure ;
b) Moon phases.
Active class of information sources allows getting the most accurate picture of the employee’s state in terms of the working day and achieve maximum individualization of the work schedule, load level, type of rest and nutrition, as well as methods of maintaining the phases of activity and rest. This class of information sources implies the use of the most relevant technologies for monitoring the physical and psychological state of an employee, and includes the following methods:
1) The temperature of individual parts of the body.
a) Heartbeat and ECG;
b) Blood pressure.
3) Brain activity.
4) Physical activity:
a) Monitoring posture, head position;
b) Monitoring obsessive (parasitic) movements.
5) Biological parameters:
a) Hormone monitoring;
b) Blood test;
c) Perspiration rate.
6) Eye tracking.
7) Sound recording and speech recognition.
8) Indoor Positioning System.
An autonomous class includes all of the above sources of information in relation to an employee. Its peculiarity lies in compiling an actual picture throughout a person’s life to achieve the greatest accuracy and effect of the system. The following points of interest are added to the already generated list of information sources:
1) Monitoring emotional state;
2) Event Logging;
3) Logging actions;
4) Logging the opinions of others.
III. Research Methods
At this stage it is planned to conduct a series of experiments to formulate and prove possible scenarios of impact methods application considering collected data. There is a number of possible job types or niches available for the implementation of SEMS. In order to determine the most suitable option for the first experiments next criteria were considered:
1) This niche is being sponsored (by government or private companies);
2) This niche is ready for scientific experiments and improving currently existing results using innovative approaches;
3) It is possible to formulate a clear business case, i. e. determining the impact of integration of SEMS on company profit or cost reduction;
4) It is required to provide the person help to achieve highest productivity at the right mo- ments(periodically) with high concentration, to pro-vide relaxation and a smooth transition between them;
5) The participant-employee-consumer takes part individually or semi-individually, i. e. it is possible to act on it personally (preferably isolated);
6) The participant-employee-consumer should be sta-tionary or semi-stationary, i. e. all equipment can be easily placed at the workplace;
7) The ongoing activity is at the junction of manual labor and brain activity.
At this point a list of possible jobs were analysed, including:
• Truck driver, plane pilot;
• Race driver;
• E-sports player;
• Air traffic controller;
• Analyst, trader;
• CAD engineer, programmer;
It was decided that electronic sports as a niche fits the most to all the listed criteria. In addition, using virtual video game engine, it is possible to obtain detailed information on player’s activity as well as virtual environment. Ability to access additional information of player’s actions, accuracy and overall performance would significantly increase the quality of research.
All the experiment method details are being formed in order to conduct quality data for further research. The big picture of the SEMS system consist of four cycled key stages (Figure 1):
Figure 1. SEMS algorithm.
1) Collecting data using the information sources;
2) Data processing and forming individual scenarios;
3) Proactive adjustment using the impact methods;
4) Learning by comparing the feedback from system after using impact methods.
In our further research it is planned to use next information sources (and equipment) during the experiments:
1) Brain data activity (Brain activity headset);
2) Breath rate (Breath rate wearable sensor);
3) Eye-tracking (Tobii Eye Tracker 4C);
4) Heart rate (Garmin chest HRM & wristband HRM).
Such information sources can provide enough data to analyse current player’s excitement, concentration, awareness and physical stress levels.
At this stage collecting real-time data based on changes in player activity and game process provides understanding on what kind of stress events results in changing this parameters. After the experiments is conducted, it is planned to determine which of the information sources are most relevant.
Next mandatory step is to form up scenarios for proactive adjustment of the environment. In our case is is decided to use minimal impact actors (and equipment), including:
1) Air temperature and flow speed (Adaptive Conditioning);
2) Lighting color and intensity (Smart LED);
3) Smells (Aroma-humidifiers);
4) Sounds and Music (Headphones);
5) Kinaesthetics (Massage chair & warming/cooling pad).
All the impact actors would be controlled with a central unit using the real-time data and results obtained on the previous stage (Figure 2). In our further experiments key components are used:
• Personal gaming computer;
• Central control and communication unit;
• A set of wearable and stationary sensors;
• A set of impact actors.
Figure 2. SEMS prototype architecture.
As a result of this research work it is planned to formulate a number of scenarios according to which it is possible to use various available data and actors in order to increase productivity with the least harming effect for the health in the long-term perspective.
Using Smart Ergonomics approach it is possible to achieve higher results in many sport disciplines. SEMS can significantly improve training process by providing detailed understanding of sportsman’s biorhythms, measuring physical condition in real-time, providing individual plans and helping to achieve needed physical condition throughout the training process. Implementation of SEMS system in active sports would require more compact wearable sensors and impact actors. In addition, this system can be applied to existing Cyclic Variations in Adaptive Conditioning systems to benefit in effectiveness of the training.
Smart Ergonomics concept can also find it’s use in such fundamental area such as medicine. We consider using SEMS system as an additional module for life-supporting systems in order to achieve maximum treatment effectiveness or as a solution for home-based treatment or profilaxy that can help following the treatment procedure without the need of direct supervision or assistance of a professional staff members.
Another promising use of Smart Ergonomics concept is the ability to determine the correlation between individual’s stress level and daily life bad habits. This can be used in order to maintain needed for person comfort level and exclude necessity in some of the harmful in the long-term perspective bad habits such as smoking or alcohol addiction considering their proved relaxation effect.
In the future, it is planned to increase the level of automation of SEMS by providing standards for general consumer Internet-of-Things (IoT) products manufacturing companies. It is possible to use common wearable and stationary IoT products on the market that can form person’s physical and psychological conditions avatar by cooperatively providing accessible information in a cloud or other local unit. For instance many products like wearable sport trackers, smart shoe soles, smartphones, eye-trackers, brain activity headsets, indoor cameras, car driver smart assistants and other units can provide data that can then be used in SEMS.
In marketing, the key goal is to understand individual preferences of the potential consumer and offer most relevant at the moment product. A lot of principles of understanding general user marketing profile by analyzing social networks and other activity information is currently observed. However, offering a product without understanding actual condition of your potential client inevitably lowers the conversion rate. Smart Ergonomics can help achieving new level of user preferences determination precision level for marketing purpose. It can be achieved by analyzing consumer’s condition in realtime, what makes it possible to understand actual emotions and feelings at the moment and achieve highest precision in marketing.
In this work we consider providing optimal conditions that can lead to decreasing person’s overall stress level. It is stated that for harmonious and consistent development of human potential, a particular level of stress remains vital. Elimination of stress from our daily life can negatively affect on our self-development progress. On the other hand, if we provide controllable amount of stress using the SEMS system, it is possible to achieve higher results in human potential growth .
As a result of the work, the basic principles of the Smart Ergonomics concept and the Smart Ergonomics Management System are formulated. Impact methods and information sources are analyzed and classified in details and a number of scientific materials with the justification of the principles is provided. The research methods for the future experiments as well as detailed information on available equipment and planned results are described.
Short-term plans include the development of the Smart Ergonomics Management System in terms of e-sports disciplines as well as finding more scientific works regarding information sources, effect methods and scenarios. It is planned to establish collaboration with a number of international companies and universities that cover research and development of socio-cyber-physical systems. With the growing interest in Smart Ergonomics concept, a new line for scientific work can be formed.
By collaborating with other institutions a quality of research would be increased. Cooperation with companies can speed up the prototyping process and enhance research results and finally form up a new market niche. Long-term plans include an investigation of usability of Smart Ergonomics concept in terms of education, healthcare, sport and marketing. As it was stated, Smart Ergonomics can find it’s use in many types of daily life activity and would significantly help in development of human potential.
 Acemoglu, D. and Restrepo, P. Automation and new tasks: How technology displaces and reinstates labor, in Journal of Economic Perspectives, May 2019, vol. 33, no. 2, pp. 3–30 [Online]. Available at: https://www.aeaweb.org/articles?id=10.1257/j ep. 33.2.3
 Maier, T., Monnig, A., and Zika, G. Labour demand in Germany by industrial sector, occupational field and qualification until 2025— model calculations using the IAB/INFORGE model, in Economic Systems Research, 2015, vol. 27, no. 1, pp. 19–42 [Online]. Available at: https://doi.org/10.1080/09535314.2014.997678
 Vedaa, Ǿ., Krossbakken, E., Grimsrud, I. D., Bjorvatn, B., Sivertsen, B., Magerøy, N., Einarsen, S., and Pallesen, S. Prospective study of predictors and consequences of insomnia: personality, lifestyle, mental health, and work-related stressors, in Sleep Medicine, 2016, vol. 20, pp. 51–58 [Online]. Available at: http://www.sciencedirect.com/science/article/pii/S1389945715020766
 Halkos, G. and Bousinakis, D. The effect of stress and satisfaction on productivity, in International Journal of Prod uctivity and Performance Management, 2010
 Poulton, E. The environment at work, in Applied Ergonomics, 1972, vol. 3, no. 1, pp. 24–29 [Online]. Available at: http://www.sciencedirect.com/science/article/pii/0003687072900075
 Vehvilainen, T., Lindholm, H., Rintamaki, H., Paakkonen, R., Hirvonen, A., Niemi, O., and Vinha, J. High indoor co2 concentrations in an office environment increases the transcutaneous co2 level and sleepiness during cognitive work, in Journal of occupational and environmental hygiene, 2016, vol. 13, no. 1, pp. 19–29
 Terman, M. and Terman, J. S. Controlled trial of naturalistic dawn simulation and negative air ionization for seasonal affective disorder, in American Journal of Psychiatry, 2006, vol. 163, no. 12, pp. 2126–2133
 He, J., Liu, H. and Salvo, A. Severe air pollution and labor productivity: Evidence from industrial towns in china, in American Economic Journal: Ap plied Economics, January 2019, vol. 11, no. 1, pp. 173–201 [Online]. Available at: https://www.aeaweb.org/articles?id=10.1257/app.20170286
 Wolkoff, P. and Kjsrgaard, S. K. The dichotomy of relative humidity on indoor air quality, in Environment International, 2007, vol. 33, no. 6, pp. 850–857 [Online]. Available at: http://www.sciencedirect.com/science/article/pii/S0160412007000773
 Abdou, O. A. Effects of Luminous environment on worker productivity in building spaces, in Journal of architectural engineering, 1997, vol. 3, no. 3, pp. 124–132
 Mak, C. M. and Lui, Y. The effect of sound on office productivity, in Building Services Engineering Research and Technology, 2012, vol. 33, no. 3, pp. 339–345
 Rosekind, M. R., Gregory, K. B., Mallis, M. M., Brandt, S. L., Seal, B., and Lerner, D. The cost of poor sleep: workplace productivity loss and associated costs, in Journal of Occupational and Environmental Medicine, 2010, vol. 52, no. 1, pp. 91–98
 Pilcher, J. J., Ginter, D. R., and Sadowsky, B. Sleep quality versus sleep quantity: relationships between sleep and measures of health, well-being and sleepiness in college students, in Journal of psychosomatic research, 1997, vol. 42, no. 6, pp. 583–596
 Popkin, B. M. Nutrition and labor productivity, Social Science & Medicine. Part C: Medical Economics, 1978, vol. 12, no. 1, pp. 117–125 [Online]. Available at: http://www.sciencedirect.com/science/article/pii/016079957890028X/
 Zubek, J. and Jackson, C. Sensory Deprivation: Fifteen Years of Research, ser. Century psychology series. Appleton-Century-Crofts, 1969 [Online]. Available at: https://books.google.ru/books?id=1tBZauKc4GUC
 Cox, M., Shephard, R. J., and Corey, P. Influence of an employee fitness programme upon fitness, productivity and absenteeism, in Ergonomics, 1981, vol. 24, no. 10, pp. 795–806. pMID: 7318813. [Online]. Available at: https://doi.org/10.1080/00140138108924900
 Reeves, B. and Read, J. Total Engagement: How Games and Virtual Worlds Are Changing the Way People Work and Businesses Compete, Harvard Business Review Press, 2009. [Online]. Available at: https://books.google.ru/books?id=hbFSia7bdUoC
 Ali, B., Al-Wabel, N. A., Shams, S., Ahamad, A., Khan, S. A., and Anwar, F. Essential oils used in aromatherapy: A systemic review, in Asian Pacific Journal of Tropical Biomedicine, 2015, vol. 5, no. 8, pp. 601–611 [Online]. Available at: http://www.sciencedirect.com/science/article/pii/S2221169115001033
 Shin, J.-Y., Chun, S.-Y., and Lee, C.-S. Analysis of the effect on attention and relaxation level by correlated color temperature and illuminance of led lighting using eeg signal, in Journal of the Korean Institute of Illuminating and Electrical Installation Engineers, 2013, vol. 27, no. 5, pp. 9–17
 Juslén, H. Lighting, productivity and preferred illuminances: field studies in the industrial environment; valaistus, tuot- tavuus ja valaistusvoimakkuusmieltymykset — kenttakokeita teollisu-usympäristössä, G5 Artikkelivaitoskirja, Helsinki University of Technology; Teknillinen korkeakoulu, 2007–10–19. [Online]. Available at: http://urn.fi/urn: nbn: fi: tkk-010578
 Juslén, H., Wouters, M., and Tenner, A. The influence of controllable task-lighting on productivity: a field study in a factory, in Applied Ergonomics, 2007, vol. 38, no. 1, pp. 39–44 [Online]. Available at: http://www.sciencedirect.com/science/article/pii/S0003687006000160
 Grigore, O., Gavat, I., Grigore, C., and Cotescu, M. An adaptive lighting system using the simulated annealing algorithm, in 8th conference on Simulation, modelling and optimization, 2008, pp. 142–147
 Niemela, R., Hannula, M., Rautio, S., Reijula, K., and Railio, J. The effect of air temperature on labour productivity in call centres — a case study, in Energy and Buildings, 2002, vol. 34, no. 8, pp. 759–764, rEHVA Scientific. [Online]. Available at: http://www.sciencedirect.com/science/article/pii/S0378778802000944
 Kawakami, M., Aoki, S., and Ohkubo, T. A study of ‚fragrance‘ on working environment characteristics in VDT work activities, in International Journal of Production Economics, 1999, vol. 60–61, pp. 575–581 [Online]. Available at: http://www.sciencedirect.com/science/article/pii/S0925527398001364
 Warrenburg, S. Effects of fragrance on emotions: Moods and physiology, in Chemical Senses, vol. 30, no. suppl_1, 01/ 2005, pp. i248–i249 [Online]. Available at: https://doi.org/10.1093/chemse/bjh208
 Ratcliffe, E., Gatersleben, B., and Sowden, P. T. Bird sounds and their contributions to perceived attention restoration and stress recovery, in Journal of Environmental Psychology, 2013, vol. 36, pp. 221–228 [Online]. Available at: http://www.sciencedirect.com/science/article/pii/S0272494413000650
 Lee, E.-J., Bhattacharya, J., Sohn, C., and Verres, R. Monochord sounds and progressive muscle relaxation reduce anxiety and improve relaxation during chemotherapy: A pilot eeg study, in Complementary Therapies in Medicine, 2012, vol. 20, no. 6, pp. 409–416 [Online]. Available at: http://www.sciencedirect.com/science/article/pii/S096522991200088X
 Barratt, E. L., and Davis, N. J. Autonomous sensory meridian response (ASMR): a flow-like mental state, in PeerJ, 2015, vol. 3, p. 851
 Lochte, B. C., Guillory, S. A., Richard, C. A., and Kelley, W. M. An fMRI investigation of the neural correlates underlying the autonomous sensory meridian response (ASMR), in BioImpacts: BI, 2018, vol. 8, no. 4, p. 295
 Shulman, K. R. and Jones, G. E. The effectiveness of massage therapy intervention on reducing anxiety in the workplace, in The Journal of Applied Behavioral Science, 1996, vol. 32, no. 2, pp. 160–173 [Online]. Available at: https://doi.org/10.1177/0021886396322003
 PhD, T. K., MSc, R. S. K., MSc, S. J. L., PhD, T. H., and PhD, R. S. J. T. The direct impact of climate change on regional labor productivity, in Archives of Environmental & Occupational Health, 2009, vol. 64, no. 4, pp. 217–227 pMID: 20007118. [Online]. Available at: https://doi.org/10.1080/19338240903352776
 Saunders, T., Driskell, J. E., Johnston, J. H., and Salas, E. The effect of stress inoculation training on anxiety and performance, in Journal of occupational health psychology, 1996, vol. 1, no. 2, p. 170