Effects of indoor temperature on office workers' performance: an experimental study based on subjective assessments, neurobehavioral tests, and physiological measurements

Indoor temperature has a critical impact on the performance of office workers. This study aimed to evaluate the effect of indoor temperature on work performance through subjective assessments, neurobehavioral tests, and physiological measurements. The experiment was conducted in a controlled office environment. Under each temperature condition, participants voted on their perception of thermal sensation, thermal satisfaction, and sick building syndrome (SBS) symptoms. Participants were given neurobehavioral tests based on a ten-item task, and their body temperature, blood pressure, heart rate, and blood oxygen saturation were measured before and after the tests. The study showed that the effect of indoor temperature on the test tasks varied greatly and depended on the task type. The indoor temperature, thermal sensation votes, and body temperature for optimum work performance were 17 °C, -0.57, and 36.4 °C, respectively. Work performance was positively correlated with thermal satisfaction votes and negatively correlated with sleepiness intensity.Practitioner summary: Work performance is closely related to indoor temperature. This study evaluated the effect of indoor temperature on work performance through subjective assessments, neurobehavioral tests, and physiological measurements. The relationships between work performance and indoor temperature, perceived votes, and physiological parameters were established, respectively.

Methods and evaluation of physiological measurements with acoustic stimuli-a systematic review

Objective. The detection of psychological loads, such as stress reactions, is receiving greater attention and social interest, as stress can have long-term effects on health O'Connor, Thayer and Vedhara (2021Ann. Rev. Psychol.72, 663-688). Acoustic stimuli, especially noise, are investigated as triggering factors. The application of physiological measurements in the detection of psychological loads enables the recording of a further quantitative dimension that goes beyond purely perceptive questionnaires. Thus, unconscious reactions to acoustic stimuli can also be captured. The numerous physiological signals and possible experimental designs with acoustic stimuli may quickly lead to a challenging implementation of the study and an increased difficulty in reproduction or comparison between studies. An unsuitable experimental design or processing of the physiological data may result in conclusions about psychological loads that are not valid anymore.Approach. The systematic review according to the preferred reporting items for systematic reviews and meta-analysis standard presented here is therefore intended to provide guidance and a basis for further studies in this field. For this purpose, studies were identified in which the participants' short-term physiological responses to acoustic stimuli were investigated in the context of a listening test in a laboratory study.Main Results. A total of 37 studies met these criteria and data items were analysed in terms of the experimental design (studied psychological load, independent variables/acoustic stimuli, participants, playback, scenario/context, duration of test phases, questionnaires for perceptual comparison) and the physiological signals (measures, calculated features, systems, data processing methods, data analysis methods, results). The overviews show that stress is the most studied psychological load in response to acoustic stimuli. An ECG/PPG system and the measurement of skin conductance were most frequently used for the detection of psychological loads. A critical aspect is the numerous different methods of experimental design, which prevent comparability of the results. In the future, more standardized methods are needed to achieve more valid analyses of the effects of acoustic stimuli.

Direct estimation of central aortic pressure from measured or quantified mean and diastolic brachial blood pressure: agreement with invasive records

Background

Recently it has been proposed a new approach to estimate aortic systolic blood pressure (aoSBP) without the need for specific devices, operator-dependent techniques and/or complex wave propagation models/algorithms. The approach proposes aoSBP can be quantified from brachial diastolic and mean blood pressure (bDBP, bMBP) as: aoSBP = bMBP2/bDBP. It remains to be assessed to what extent the method and/or equation used to obtain the bMBP levels considered in aoSBP calculation may affect the estimated aoSBP, and consequently the agreement with aoSBP invasively recorded.

Methods

Brachial and aortic pressure were simultaneously obtained invasively (catheterization) and non-invasively (brachial oscillometry) in 89 subjects. aoSBP was quantified in seven different ways, using measured (oscillometry-derived) and calculated (six equations) mean blood pressure (MBP) levels. The agreement between invasive and estimated aoSBP was analyzed (Concordance correlation coefficient; Bland-Altman Test).

Conclusions

The ability of the equation "aoSBP = MBP2/DBP" to (accurately) estimate (error <5 mmHg) invasive aoSBP depends on the method and equation considered to determine bMBP, and on the aoSBP levels (proportional error). Oscillometric bMBP and/or approaches that consider adjustments for heart rate or a form factor ∼40% (instead of the usual 33%) would be the best way to obtain the bMBP levels to be used to calculate aoSBP.

1-Year Outcomes of Blinded Physiological Assessment of Residual Ischemia After Successful PCI: DEFINE PCI Trial

OBJECTIVES

The aim of this study was to identify the post-percutaneous coronary intervention (PCI) target value of instantaneous wave-free ratio (iFR) that would best discriminate clinical events at 1 year in the DEFINE PCI (Physiologic Assessment of Coronary Stenosis Following PCI) study.

BACKGROUND

The impact of residual ischemia detected by iFR post-PCI on clinical and symptom-related outcomes is unknown.

METHODS

Blinded iFR pull back was performed after successful stent implantation in 500 patients. The primary endpoint was the rate of residual ischemia, defined as iFR ≤0.89, after operator-assessed angiographically successful PCI. Secondary endpoints included clinical events at 1 year and change in Seattle Angina Questionnaire angina frequency (SAQ-AF) score during follow-up.

RESULTS

As reported, 24.0% of patients had residual ischemia (iFR ≤0.89) after successful PCI, with 81.6% of cases attributable to angiographically inapparent focal lesions. Post-PCI iFR ≥0.95 (present in 182 cases [39%]) was associated with a significant reduction in the composite of cardiac death, spontaneous myocardial infarction, or clinically driven target vessel revascularization compared with post-PCI iFR <0.95 (1.8% vs 5.7%; P = 0.04). Baseline SAQ-AF score was 73.3 ± 22.8. For highly symptomatic patients (baseline SAQ-AF score ≤60), SAQ-AF score increased by ≥10 points more frequently in patients with versus without post-PCI iFR ≥0.95 (100.0% vs 88.5%; P = 0.01).

CONCLUSIONS

In DEFINE PCI, despite angiographically successful PCI, highly symptomatic patients at baseline without residual ischemia by post-PCI iFR had greater reductions in anginal symptoms at 1 year compared with patients with residual ischemia. Achieving post-PCI iFR ≥0.95 was also associated with improved 1-year event-free survival. (Physiologic Assessment of Coronary Stenosis Following PCI [DEFINE PCI]; NCT03084367).

Whole body massage for newborns: A report on non-invasive methodology for neonatal opioid withdrawal syndrome

BACKGROUND

Infants with in-utero exposure to opioids are at risk Neonatal Opioid Withdrawal Syndrome (NOWS) and non-pharmacological methods of care, like swaddling, quiet ambient environment are routinely recommended but are not systematically studied. We hypothesized that opioid exposed infants can tolerate whole body massage while hospitalized.

METHODS

This is a prospective observational study (August 2017 to January 2019) and infants of mothers having a history of opioids use (OUD) were included. Infants received whole body massage for 30 minutes from birth till discharge home. Infants heart rate (HR), respiratory rate (RR), systolic (sBP) and diastolic blood pressure (dBP) were recorded prior to and at the end of massage session.

RESULTS

The pilot study enrolled 30 infants. The mean birth weight and gestational age were 38±1 weeks and 2868±523 grams, respectively. All massage sessions were well tolerated. There was marked decrease in HR, systolic and diastolic BP and RR, (p < 0.01) in all study infants post massage, more profound among infants with NOWS (p < 0.01) than without NOWS.

CONCLUSIONS

Whole body massage is very well tolerated by infants with in-utero opioid exposure. Infants with NOWS had marked decrease in their HR and BP from their baseline after massage.

Automated affect classification and task difficulty adaptation in a competitive scenario based on physiological linkage: An exploratory study

In competitive and cooperative scenarios, task difficulty should be dynamically adapted to suit people with different abilities. State-of-the-art difficulty adaptation methods for such scenarios are based on task performance, which conveys little information about user-specific factors such as workload. Thus, we present an exploratory study of automated affect recognition and task difficulty adaptation in a competitive scenario based on physiological linkage (covariation of participants' physiological responses). Classification algorithms were developed in an open-loop study where 16 pairs played a competitive game while 5 physiological responses were measured: respiration, skin conductance, electrocardiogram, and 2 facial electromyograms. Physiological and performance data were used to classify four self-reported variables (enjoyment, valence, arousal, perceived difficulty) into two or three classes. The highest classification accuracies were obtained for perceived difficulty: 84.3% for two-class and 60.5% for three-class classification. As a proof of concept, the developed classifiers were used in a small closed-loop study to dynamically adapt game difficulty. While this closed-loop study found no clear advantages of physiology-based adaptation, it demonstrated the technical feasibility of such real-time adaptation. In the long term, physiology-based task adaptation could enhance competition and cooperation in many multi-user settings (e.g., education, manufacturing, exercise).

User Experience With Dynamic Difficulty Adjustment Methods for an Affective Exergame: Comparative Laboratory-Based Study

BACKGROUND

In affective exergames, game difficulty is dynamically adjusted to match the user's physical and psychological state. Such an adjustment is commonly made based on a combination of performance measures (eg, in-game scores) and physiological measurements, which provide insight into the player's psychological state. However, although many prototypes of affective games have been presented and many studies have shown that physiological measurements allow more accurate classification of the player's psychological state than performance measures, few studies have examined whether dynamic difficulty adjustment (DDA) based on physiological measurements (which requires additional sensors) results in a better user experience than performance-based DDA or manual difficulty adjustment.

OBJECTIVE

This study aims to compare five DDA methods in an affective exergame: manual (player-controlled), random, performance-based, personality-performance-based, and physiology-personality-performance-based (all-data).

METHODS

A total of 50 participants (N=50) were divided into five groups, corresponding to the five DDA methods. They played an exergame version of Pong for 18 minutes, starting at a medium difficulty; every 2 minutes, two game difficulty parameters (ball speed and paddle size) were adjusted using the participant's assigned DDA method. The DDA rules for the performance-based, personality-performance-based, and all-data groups were developed based on data from a previous open-loop study. Seven physiological responses were recorded throughout the sessions, and participants self-reported their preferred changes to difficulty every 2 minutes. After playing the game, participants reported their in-game experience using two questionnaires: the Intrinsic Motivation Inventory and the Flow Experience Measure.

RESULTS

Although the all-data method resulted in the most accurate changes to ball speed and paddle size (defined as the percentage match between DDA choice and participants' preference), no significant differences between DDA methods were found on the Intrinsic Motivation Inventory and Flow Experience Measure. When the data from all four automated DDA methods were pooled together, the accuracy of changes in ball speed was significantly correlated with players' enjoyment (r=0.38) and pressure (r=0.43).

CONCLUSIONS

Although our study is limited by the use of a between-subjects design and may not generalize to other exergame designs, the results do not currently support the inclusion of physiological measurements in affective exergames, as they did not result in an improved user experience. As the accuracy of difficulty changes is correlated with user experience, the results support the development of more effective DDA methods. However, they show that the inclusion of physiological measurements does not guarantee a better user experience even if it yields promising results in offline cross-validation.

The Impact of Heat Stress on Morpho-Physiological Response and Expression of Specific Genes in the Heat Stress-Responsive Transcriptional Regulatory Network in Brassica oleracea

Knowledge of heat-tolerant/sensitive cultivars based on morpho-physiological indicators and an understanding of the action and interaction of different genes in the molecular network are critical for genetic improvement. To screen these indicators, the physiological performance of two different varieties of white and red cabbages (B. oleracea var. capitate f. alba and f. rubra, respectively) under heat stress (HS) and non-stress (NS) was evaluated. Cultivars that showed considerable cell membrane thermostability and less reduction in chlorophyll content with better head formation were categorized as the heat-tolerant cultivars (HTC), while those with reduction in stomatal conductance, higher reduction incurred in chlorophyll and damage to thylakoid membranes are categorized as the heat-sensitive cultivars (HSC). Expression profiling of key genes in the HS response network, including BoHSP70 (HEAT SHOCK PROTEIN 70), BoSCL13 (SCARECROW-LIKE 13) and BoDPB3-1 (transcriptional regulator DNA POLYMERASE II SUBUNIT B3-1 (DPB3-1))/NUCLEAR FACTOR Y SUBUNIT C10 (NF-YC10), were evaluated in all cultivars under HS compared to NS plants, which showed their potential as molecular indicators to differentiate HTC from HSC. Based on the results, the morphophysiological and molecular indicators are applicable to cabbage cultivars for differentiating HTC from HSC, and potential target genes for genome editing were identified for enhancing food security in the warmer regions of the world.

Classification of Multiple Psychological Dimensions in Computer Game Players Using Physiology, Performance, and Personality Characteristics

Human psychological (cognitive and affective) dimensions can be assessed using several methods, such as physiological or performance measurements. To date, however, few studies have compared different data modalities with regard to their ability to enable accurate classification of different psychological dimensions. This study thus compares classification accuracies for four psychological dimensions and two subjective preferences about computer game difficulty using three data modalities: physiology, performance, and personality characteristics. Thirty participants played a computer game at nine difficulty configurations that were implemented via two difficulty parameters. In each configuration, seven physiological measurements and two performance variables were recorded. A short questionnaire was filled out to assess the perceived difficulty, enjoyment, valence, arousal, and the way the participant would like to modify the two difficulty parameters. Furthermore, participants’ personality characteristics were assessed using four questionnaires. All combinations of the three data modalities (physiology, performance, and personality) were used to classify six dimensions of the short questionnaire into either two, three or many classes using four classifier types: linear discriminant analysis, support vector machine (SVM), ensemble decision tree, and multiple linear regression. The classification accuracy varied widely between the different psychological dimensions; the highest accuracies for two-class and three-class classification were 97.6 and 84.1%, respectively. Normalized physiological measurements were the most informative data modality, though current game difficulty, personality and performance also contributed to classification accuracy; the best selected features are presented and discussed in the text. The SVM and multiple linear regression were the most accurate classifiers, with regression being more effective for normalized physiological data. In the future, we will further examine the effect of different classification approaches on user experience by detecting the user’s psychological state and adapting game difficulty in real-time. This will allow us to obtain a complete picture of the performance of affect-aware systems in both an offline (classification accuracy) and real-time (effect on user experience) fashion.

Identifying the Causes of Drivers' Hazardous States Using Driver Characteristics, Vehicle Kinematics, and Physiological Measurements

Drivers’ hazardous physical and mental states (e.g., distraction, fatigue, stress, and high workload) have a major effect on driving performance and strongly contribute to 25–50% of all traffic accidents. They are caused by numerous factors, such as cell phone use or lack of sleep. However, while significant research has been done on detecting hazardous states, most studies have not tried to identify the causes of the hazardous states. Such information would be very useful, as it would allow intelligent vehicles to better respond to a detected hazardous state. Thus, this study examined whether the cause of a driver’s hazardous state can be automatically identified using a combination of driver characteristics, vehicle kinematics, and physiological measures. Twenty-one healthy participants took part in four 45-min sessions of simulated driving, of which they were mildly sleep-deprived for two sessions. Within each session, there were eight different scenarios with different weather (sunny or snowy), traffic density and cell phone usage (with or without cell phone). During each scenario, four physiological (respiration, electrocardiogram, skin conductance, and body temperature) and eight vehicle kinematics measures were monitored. Additionally, three self-reported driver characteristics were obtained: personality, stress level, and mood. Three feature sets were formed based on driver characteristics, vehicle kinematics, and physiological signals. All possible combinations of the three feature sets were used to classify sleep deprivation (drowsy vs. alert), traffic density (low vs. high), cell phone use, and weather conditions (foggy/snowy vs. sunny) with highest accuracies of 98.8%, 91.4%, 82.3%, and 71.5%, respectively. Vehicle kinematics were most useful for classification of weather and traffic density while physiology and driver characteristics were useful for classification of sleep deprivation and cell phone use. Furthermore, a second classification scheme was tested that also incorporates information about whether or not other causes of hazardous states are present, though this did not result in higher classification accuracy. In the future, these classifiers could be used to identify both the presence and cause of a driver’s hazardous state, which could serve as the basis for more intelligent intervention systems.

Effects of swaddled and traditional tub bathing methods on crying and physiological responses of newborns

PURPOSE

The purpose of this study was to examine the effects of two bathing methods on crying duration and physiological measurements of newborns.

DESIGN AND METHODS

A randomized trial design was used in this study. The sample consisted of newborns (n = 80) who were admitted to neonatal intensive care unit of a university hospital located in a large city. The groups were determined as swaddled bathing (SB) (n = 40) and traditional tub bathing (TTB) (n = 40) by using random number table. All newborns were bathed 24 hours after the birth. Environmental variables were organised identically in both experimental and control groups. Duration of bathing was determined as maximum 5 min in both groups. Body temperature, heart rate (HR), and O₂ saturation values were evaluated before bath, just after the bath and at 10 min after the bath. The groups were compared in terms of all vital symptoms and duration of crying during bath. Pre-bath and post-bath stress levels between newborns in both groups were compared by using the Newborn Infant Pain Scale (NIPS).

RESULTS

When the newborns were compared based on groups, it was observed that there was no statistically significant difference between SB and TTB groups in terms of the gestational week, APGAR score, postnatal age, and body weight. Body temperatures of the newborns in SB group just after the bath and 10 minutes after the bath were significantly higher than those in TTB group. HR was higher in TTB group in the post-bath period. NIPS scores of the newborns in SB group after bath decreased at a statistically significant level, but the scores of the newborns in TTB group increased. The results of the study indicated that SB was effective in maintaining body temperature, SpO₂ level, and HR of newborns within normal limits and may decrease stress experienced during the bath.

PRACTICE IMPLICATIONS

Swaddled bathing decreases behavioural stress symptoms such as crying, agitation, and pulling arms and legs back unintentionally and thus the infants feel relaxed. Swaddled bathing can be recommended because swaddled bathing method decreases behavioural stress symptoms in infants.

Use of predictive algorithms in-home monitoring of chronic obstructive pulmonary disease and asthma: A systematic review

Major reported factors associated with the limited effectiveness of home telemonitoring interventions in chronic respiratory conditions include the lack of useful early predictors, poor patient compliance and the poor performance of conventional algorithms for detecting deteriorations. This article provides a systematic review of existing algorithms and the factors associated with their performance in detecting exacerbations and supporting clinical decisions in patients with chronic obstructive pulmonary disease (COPD) or asthma. An electronic literature search in Medline, Scopus, Web of Science and Cochrane library was conducted to identify relevant articles published between 2005 and July 2015. A total of 20 studies (16 COPD, 4 asthma) that included research about the use of algorithms in telemonitoring interventions in asthma and COPD were selected. Differences on the applied definition of exacerbation, telemonitoring duration, acquired physiological signals and symptoms, type of technology deployed and algorithms used were found. Predictive models with good clinically reliability have yet to be defined, and are an important goal for the future development of telehealth in chronic respiratory conditions. New predictive models incorporating both symptoms and physiological signals are being tested in telemonitoring interventions with positive outcomes. However, the underpinning algorithms behind these models need be validated in larger samples of patients, for longer periods of time and with well-established protocols. In addition, further research is needed to identify novel predictors that enable the early detection of deteriorations, especially in COPD. Only then will telemonitoring achieve the aim of preventing hospital admissions, contributing to the reduction of health resource utilization and improving the quality of life of patients.

Assessment of Mental, Emotional and Physical Stress through Analysis of Physiological Signals Using Smartphones

Determining the stress level of a subject in real time could be of special interest in certain professional activities to allow the monitoring of soldiers, pilots, emergency personnel and other professionals responsible for human lives. Assessment of current mental fitness for executing a task at hand might avoid unnecessary risks. To obtain this knowledge, two physiological measurements were recorded in this work using customized non-invasive wearable instrumentation that measures electrocardiogram (ECG) and thoracic electrical bioimpedance (TEB) signals. The relevant information from each measurement is extracted via evaluation of a reduced set of selected features. These features are primarily obtained from filtered and processed versions of the raw time measurements with calculations of certain statistical and descriptive parameters. Selection of the reduced set of features was performed using genetic algorithms, thus constraining the computational cost of the real-time implementation. Different classification approaches have been studied, but neural networks were chosen for this investigation because they represent a good tradeoff between the intelligence of the solution and computational complexity. Three different application scenarios were considered. In the first scenario, the proposed system is capable of distinguishing among different types of activity with a 21.2% probability error, for activities coded as neutral, emotional, mental and physical. In the second scenario, the proposed solution distinguishes among the three different emotional states of neutral, sadness and disgust, with a probability error of 4.8%. In the third scenario, the system is able to distinguish between low mental load and mental overload with a probability error of 32.3%. The computational cost was calculated, and the solution was implemented in commercially available Android-based smartphones. The results indicate that execution of such a monitoring solution is negligible compared to the nominal computational load of current smartphones.