Recording Heart Rate Variability of Dairy Cows to the Cloud-Why Smartphones Provide Smart Solutions

Management of dairy heifers: Can operant conditioning be an effective and feasible tool to decrease stress and ease animals' close contact and handling?

Besides health monitoring, a regular check of dairy heifers' growth rate is desirable, but it is rarely done because procedures that require restraint and handling can be associated with substantial stress for both animals and farmers. Inexperienced heifers, especially if they are highly responsive to humans, may find restraint and handling potentially aversive. This study investigated whether training heifers of different age and responsiveness toward humans (RTH), through operant conditioning, could reduce stress in animals, ease close contact and handling, and be feasible in terms of farmers' effort. We assessed 60 Holstein heifers of 2 age classes (young, n = 29, 291 ± 39 d; old, n = 31, 346 ± 62 d) according to the avoidance distance test and classified them as confident (n = 20), neutral (n = 21), or nonconfident (n = 19). Half of the heifers of each age and RTH class were trained (n = 29), whereas the other half was not (n = 31). The trained heifers were subjected to target training for 8 sessions and positively reinforced with feed to allow being touched on the muzzle, rump, and perineum. If a heifer refused positive reinforcement, the trainer stepped back as negative reinforcement. In the last week of the experiment, the effect of training on the reaction to handling was assessed in all heifers. We measured heart rate, root mean square of successive interbeat interval differences (RMSSD), and fecal cortisol metabolites (FCMet). The presence of behavioral distress signs was recorded as well. The avoidance distance test was performed a second time 24 h after the measuring session. All of the trained heifers, regardless of RTH class, successfully accomplished the target training task in 6 sessions, each spending on average 25.3 s per session. All of the trained heifers allowed touches on the rump and perineum at the end of the fourth session. Training nonconfident heifers required more time compared with the others. Trained heifers showed higher RMSSD than nontrained heifers (14.2 vs. 16.9 ms, respectively), indicating a lower vagal tone, and thus, a slightly lower stress level than nontrained heifers. Training did not lead to differences in HR, FCMet, or presence of stress behavioral signs. Nonconfident heifers had the highest mean baseline FCMet values compared with neutral and confident heifers (38.4 vs. 30.3 vs. 29.1 ng/g, respectively). Nonconfident heifers also showed the lowest value of FCMet 12 h after the measuring session (36.7 vs. 44.6 vs. 49.7 ng/g), likely due to a decreased responsiveness of the adrenal gland to a stressor. The average avoidance distance decreased between the beginning and the end of the experiment, especially for neutral and nonconfident heifers, regardless of whether they were trained or not. These results show how using operant conditioning on some heifers not only decreased their vagal tone, but also reduced the responsiveness to humans of all the animals, trained and not trained; in the latter case, this reduction was through nonassociative learning, such as habituation.

Short-term physiological responses to moderate heat stress in grazing dairy cows in temperate climate

Even in temperate climate regions, an increase in ambient temperature and exposure to solar radiation can cause heat stress in lactating dairy cows. We hypothesised that grazing dairy cows exhibit short-term physiological changes due to increasing heat load under moderate climate conditions. Over two consecutive summers, 38 lactating Holstein dairy cows were studied in a full-time grazing system. Data were collected in 10 experimental periods of up to three consecutive days with a moderate comprehensive climate index (CCI). The individual animals' vaginal temperature (VT), heart rate, and locomotor activity data were automatically monitored with sensors. Blood samples and proportional whole milk samples were collected at afternoon milking. The concentrations of beta-hydroxybutyrate, glucose, non-esterified fatty acids, urea nitrogen, plasma thyroxine and triiodothyronine were analysed in blood plasma, and fat, protein, lactose, urea nitrogen, cortisol, Na⁺, K⁺, and Cl^- concentrations were analysed in milk. The daily distribution of VT recordings greater than 39 °C showed a circadian rhythm with a proportion of recordings of 2% and lower during the night and a percentage of 10% or higher in the afternoon. The cows' maximal daily vaginal temperature (VT_MAX) between 0830 and 1430 h was positively related to the mean daily CCI in the same time period (CCI_MEAN; mean and SD 23.6 ± 5.4 °C). Cows with greater VT_MAX had an increased mean heart rate, plasma glucose and milk cortisol concentrations and decreased concentrations of plasma thyroxine and triiodothyronine. The concentration of Na⁺ in milk was lower, and the concentration of K⁺ in milk tended to be higher in cows with increased VT_MAX. For beta-hydroxybutyrate, non-esterified fatty acids and urea nitrogen concentrations in plasma and fat and lactose concentrations in milk no relationships were found in terms of increasing VT. For milk urea nitrogen and protein concentrations, the proportion of total variance explained by inter-individual or -period variance was high. In conclusion, changes observed in milk and blood likely reflected short-term physiological responses to moderate heat stress. In particular, milk cortisol and Na⁺ may be useful traits for timely monitoring of heat stress in individual cows because their inter-individual variances were relatively small and samples can be collected non-invasively.

Technical note: A Nose Ring Sensor System to Monitor Dairy Cow Cardiovascular and Respiratory Metrics

Monitoring cardiovascular and respiratory measurements corresponds to the precision livestock farming (PLF) objective to continuously monitor and assess dairy cows' welfare and health. Changes in heart rate, breathing rate, and oxygen saturation (SpO2) are valuable metrics in human and veterinary medicine to assess stress, pain, illness, and detect critical conditions. The common way to measure heart rate is either manually or with a stethoscope. Under research conditions, heart rate is usually measured with a sports watch chest belt. Breathing rate is obtained by counting the cow's flank movements which is a time-consuming and labor-intensive method that requires training and is prone to human error. No devices are available on the market that enable practical and easy pulse oximetry in farm animals. This study presents a wireless nose ring sensor system (NoRS) composed of photoplethysmography and thermal sensors that attach to the nostrils of four Holstein dairy cows. The NoRS's thermocouple measured the cow's nasal cavity air temperature; an optic sensor measured the IR (660 nm) and RED (660 nm) signals reflected from the cow's nasal septum. Breathing was calculated from the thermocouple signal's center frequency with a Fast Fourier Transformation, or the signal peak count (i.e., oscillations). The breathing rate was compared to breathing observed by concurrently counting the flank movements. Heart rate and SpO2 were measured by integrated pulse oximetry and heart rate monitor module (MAX30101 TinyCircuit) assembled on the NoRS circuit. Heart rate was also measured with FFT and by counting the number of peaks from the optic sensor's raw IR and RED signals. These measures were compared to an off the shelf hand-held pulse oximeter's heart rate and SpO2 readings during the same time. The comparisons revealed highly significant correlations for the heart rate readings where the strength of the correlation was sensitive to the method. The correlation between breathing rate and the veterinarian's visual observations was low, albeit significant. Thus inhale-exhale cycle counting constitutes a more precise approach than flank movement counts. The hand-held device's 96% SpO2 is compatible with near-saturation values expected in healthy cows. The mean NoRS SpO2 reading was 3% less. After further piloting under field conditions, the NoRS will require no animal restraining to automatically and continuously record cows' breathing rate, heart rate, and SpO2.

Prediction of Cow Calving in Extensive Livestock Using a New Neck-Mounted Sensorized Wearable Device: A Pilot Study

In this study, new low-cost neck-mounted sensorized wearable device is presented to help farmers detect the onset of calving in extensive livestock farming by continuously monitoring cow data. The device incorporates three sensors: an inertial measurement unit (IMU), a global navigation satellite system (GNSS) receiver, and a thermometer. The hypothesis of this study was that onset calving is detectable through the analyses of the number of transitions between lying and standing of the animal (lying bouts). A new algorithm was developed to detect calving, analysing the frequency and duration of lying and standing postures. An important novelty is that the proposed algorithm has been designed with the aim of being executed in the embedded microcontroller housed in the cow’s collar and, therefore, it requires minimal computational resources while allowing for real time data processing. In this preliminary study, six cows were monitored during different stages of gestation (before, during, and after calving), both with the sensorized wearable device and by human observers. It was carried out on an extensive livestock farm in Salamanca (Spain), during the period from August 2020 to July 2021. The preliminary results obtained indicate that lying-standing animal states and transitions may be useful to predict calving. Further research, with data obtained in future calving of cows, is required to refine the algorithm.

A Multi-Disciplinary Approach to Assess the Welfare Impacts of a New Virtual Fencing Technology

Virtual fencing involving the application of audio cues and electrical stimuli is being commercially developed for cattle. Virtual fencing has the potential to improve productivity through optimized pasture management and utilization by grazing animals. The application of virtual fencing initiates public concern for the potential welfare impacts on animals due the aversive nature of using an electrical stimulus. It is therefore important to provide welfare assurance of the impacts of virtual fencing on livestock. In this paper, we provide an overview of the welfare assessment and validation stages for virtual fencing which could be applied to other new technologies utilizing novel systems. An understanding of stress measures and their suitability for use in specific contexts is discussed, including the use of glucocorticoids to measure both acute and chronic stress, and behavioral responses and patterns to indicate welfare states. The importance of individual differences in relation to learning and cognition are also highlighted. Together, this multi-disciplinary approach to welfare assessment provides a tool kit that may be applied for welfare assurance of some new technologies and systems for farm animals.

An Experimental Study of Step Test Index Combined With Heart Rate Variability in Estimating Maximum Oxygen Uptake in Women With Drug Use Disorder

BACKGROUND

Maximal oxygen uptake (VO2max), a vital physiological indicator, has been widely used in many fields. In recent years, the measurement method of VO2max has been widely explored in various populations, but few studies have been conducted for women drug abusers. For the importance of VO2max in the formulation of aerobic exercise intensity for drug users, the present study estimated VO2max using the step test index combined with heart rate variability in women with drug use disorder.

METHODS

Forty women methamphetamine (MA) users without cardiovascular disease and dyskinesia participated in a cardiopulmonary exercise test (CPX) and a 3-minute step test. Each of them performed a heart rate variability (HRV) monitoring test after the step test, and VO2max was estimated by step test index and HRV.

RESULTS

(1) The step test index had a significant positive correlation with VO2max. The standard deviation of normal-to-normal interval (SDNN) had a significant positive correlation with VO2max and a significant positive correlation with the step test index; (2) the R-square values of the estimated VO2max by step test index and post-SDNN for overall MA users were 0.29 and 0.22, with an accuracy of 93.19 and 92.85%, respectively; (3) the R-square values of the estimated VO2max by step test index and post-SDNN in group I were 0.27 and 0.36, respectively, with an accuracy of 94.04 and 93.99%. The R-square value of the estimated VO2max by step test index in group II was 0.44, with an accuracy of 92.65%, however, post-SDNN cannot adequately estimate the VO2max in group II; and (4) there was no significant difference in VO2max obtained by CPX, step test index, or post-SDNN, regardless of overall or grouping variable analysis.

CONCLUSION

The 3-minute step test combined with HRV can estimate the VO2max of women MA users to a certain extent, but the size and the coverage of the sample size should be further considered. In the future, more methods, such as machine learning or artificial neural networks, should be used.

Enhancing the Robustness of Smartphone Photoplethysmography: A Signal Quality Index Approach

Heart rate variability (HRV) provides essential health information such as the risks of heart attacks and mental disorders. However, inconvenience related to the accurate detection of HRV limits its potential applications. The ubiquitous use of smartphones makes them an excellent choice for regular and portable health monitoring. Following this trend, smartphone photoplethysmography (PPG) has recently garnered prominence; however, the lack of robustness has prevented both researchers and practitioners from embracing this technology. This study aimed to bridge the gap in the literature by developing a novel smartphone PPG quality index (SPQI) that can filter corrupted data. A total of 226 participants joined the study, and results from 1343 samples were used to validate the proposed sinusoidal function-based model. In both the correlation coefficient and Bland–Altman analyses, the agreement between HRV measurements generated by both the smartphone PPG and the reference electrocardiogram improved when data were filtered through the SPQI. Our results support not only the proposed approach but also the general value of using smartphone PPG in HRV analysis.