Zoekresultaten

Using the apple watch to teach and learn about heart rate variability while vacationing.

The war from both sides : how Dutch and German visitors experience an exhibit of Second World War stories

At the 75th anniversary of the end of the Second World War, questions arise if contemporary audiences still find historical accounts relevant. Fundamental to understanding the relevance of stories from the war is assessing their emotional impact on leisure participants from various social groups. We used the social identity theory framework to assess differences in emotional reactions of Dutch and German visitors to stories of the Second World War presented at a Dutch museum exhibit. Emotional reactions were measured using physiological signals of heart rate and heart rate variability as well as self-report. Emotions experienced were mixed and often, but not always, different between Dutch and German participants. Patterns in the physiological and self-report data differed. Many of the significant differences were generally consistent with a collective guilt account of German social identity, but the findings as a whole were more complex than could be predicted by existing social identity accounts. Specifically, participants did not simply categorize themselves with either national or human identities of characters based on what their respective stories emphasized. We conclude that stories of the Second World War are still relevant, but touch on audiences’ nationalities in a complex way, beyond simple historical categories.

Using the apple watch to teach and learn about heart rate variability while vacationing.

Exploring a 1-Minute Paced Deep-Breathing Measurement of Heart Rate Variability as Part of a Workers’ Health Assessment

Low heart rate variability (HRV) is related to health problems that are known reasons for sick-leave or early retirement. A 1-minute-protocol could allow large scale HRV measurement for screening of health problems and, potentially, sustained employability. Our objectives were to explore the association of HRV with measures of health. Cross-sectional design with 877 Dutch employees assessed during a Workers’ Health Assessment. Personal and job characteristics, workability, psychological and mental problems, and lifestyle were measured with questionnaires. Biometry was measured (BMI, waist circumference, blood pressure, glucose, cholesterol). HRV was assessed with a 1-minute paced deep-breathing protocol and expressed as mean heart rate range (MHRR). A low MHRR indicates a higher health risk. Groups were classified age adjusted for HRV and compared. Spearman correlations between raw MHRR and the other measures were calculated. Significant univariable correlations (p < 0.05) were entered in a linear regression model to explore the multivariable association with MHRR. Age, years of employment, BMI and waist circumference differed significantly between HRV groups. Significant correlations were found between MHRR and age, workability, BMI, waist circumference, cholesterol, systolic and diastolic blood-pressure and reported physical activity and alcohol consumption. In the multivariable analyses 21.1% of variance was explained: a low HRV correlates with aging, higher BMI and higher levels of reported physically activity. HRV was significantly associated with age, measures of obesity (BMI, waist circumference), and with reported physical activity, which provides a first glance of the utility of a 1-minute paced deep-breathing HRV protocol as part of a comprehensive preventive Workers’ Health Assessment.Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creat ivecommons .org/licen ses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate redit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Influence of respiration frequency on heart rate variability parameters:

BACKGROUND:Many patients visiting physiotherapists for musculoskeletal disorders face psychosocial challenges which may form a large barrier to recover. There are only a limited number of evidence based psychosocial therapies, but they are mainly based on breathing exercises. OBJECTIVE: to study which respiration frequency would lead to the highest relaxation, reflected in vagal tone derived from the heart rate variability (HRV) in healthy subjects. METHODS: A randomized controlled cross sectional study was performed. Respiration cycles of four, five, six, seven and eight breaths per minute (BPM) were delivered in randomized order for two minutes each. HRV metrics were measured during the sessions with electrocardiogram (ECG). Repeated Measures ANOVA’s were performed to analyze differences between breathing frequencies. RESULTS: 100 healthy volunteers were included (40 male). Standard Deviation of inter beat intervals (SDNN) values were significantly highest at 5 BPM, whereas the Root Mean Square of Successive Differences (RMSSD) values appeared highest at 7 breaths per minute (p< 0.01). High Frequency (HF) power was lowest at 4 BPM, whereas Low Frequency (LF) power was not significantly influenced by respiration frequency. CONCLUSIONS: Breathing at a frequency of 5 to 7 breaths per minute leads to highest HRV values, but there is no single respiration ratio that maximizes all metrics. Physiotherapists may use five to seven BPM as guidance to determine ideal breathing frequencies

Measuring heart rate with optical sensor

The problem addressed in this report is to verify the possibility of using an optical sensor in the SaxShirt in order to extract the heart rate. There are specifically three questions that we try to address. 1) How is it possible to extract heart rate (BPM) from the optical sensor? 2) Is it possible to use the sensor for extracting BPM during movement? 3) Is the heart rate measured in this way useful for measuring other higher-level parameters such as heart rate coherence and heart rate variability? For this purpose, we have performed tests with the sensor placed on different spots and the data was analyzed to see if heart rate can be extracted from the sensor measurements.