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This study sought to evaluate the accuracy of a PPG (photoplethysmography) sensor designed to measure human heart rates in monitoring the distal limb pulse of healthy adult horses. We hypothesized that the PPG sensor is sensitive to placement location and orientation, and that measurement accuracies depend on placement and orientation on the limb. To evaluate this hypothesis, a completely randomized block design with a factorial treatment structure was used. Horses were considered as the block. Limb type (right front, left front, right hind, and left hind) and position of sensor (medial or lateral) were treatments, with levels arranged in a complete (4x2) factorial design. Data were collected by placing the PPG sensor on the limb of each horse (n= 6), with placement location according to the treatment (limb type and location) combination, and taking pulse readings for 60 seconds. Manual heart rates were collected concurrently using a stethoscope. Data were analyzed by calculating root mean square errors (RMSE) for the PPG measurements with the manual heart rates as a gold standard. Variation in RMSE associated with limb and location of sensor were evaluated using a general linear model with fixed effects for limb and location and a random effect for horse. Our results indicated that the PPG sensor was ineffective at measuring horse heart rates, and that the device was insensitive to placement location and orientation. Future work should focus on developing alternative analytics to interpret the data from PPG sensors to better reflect horse heart rates.
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Brief research report: Evaluation of photoplethysmographic heart rate monitoring for sheep under heat-stressed conditions
The objective of this study was to investigate the accuracy of a wearable photoplethysmography (PPG) sensor in monitoring heart rate (HR) of sheep housed in high-temperature environments. We hypothesized that the PPG sensor would be capable of differentiating low, normal, and high HR, but would struggle to produce exact HR estimates. The sensor was open source and comprised of a microprocessor (SparkFun®ThingPlus), a photoplethysmography sensor (SparkFun® MAX30101 & MAX32664), and a data storage module (SD Card 16GB), all sewn into a nylon collar with hook-and-loop closure. Sheep (n=4) were divided into 2 groups and exposed to different thermal environments in a cross-over design. The collar was placed around the neck of the sheep during the data collection phase and the manual HR were collected twice a day using a stethoscope. Precision and accuracy of numeric heart rate estimates were analyzed in R software using Pearson correlation and root mean squared prediction errors. Random forest regression was used to classify HR based on low, medium, and high to determine opportunities to leverage the PPG sensors for HR classification. Sensitivity, specificity, and accuracy were measured to evaluate the classification approach. Our results indicated that the PPG-based sensor measured sheep HR with poor accuracy and with higher average estimates in comparison with manually measured with a stethoscope. Categorical classification of HR was also poor, with accuracies ranging from 32% to 49%. Additional work is needed focusing on data analytics, and signal optimization to further rely on PPG sensors for accurately measuring HR in sheep.
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- Award ID(s):
- 2106987
- PAR ID:
- 10469214
- Publisher / Repository:
- Frontiers
- Date Published:
- Journal Name:
- Frontiers in Animal Science
- Volume:
- 3
- ISSN:
- 2673-6225
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/fanim.2022.1046557
