Behavioral Fingerprinting: Acceleration Sensors for Identifying Changes in Livestock Health
Abstract
:1. Introduction
2. Behavioral Indicators of Animal Health
2.1. Eating
2.2. Ruminating
2.3. Physical Activity
2.3.1. Active Behavior
2.3.2. Inactive Behavior
2.3.3. Expressive Behavior
3. Acceleration Sensors for Measurement of Behavioral Patterns
3.1. Ear-Attached Accelerometers
3.2. Jaw-Mounted Accelerometers
3.3. Collar-Mounted Accelerometers
3.4. Leg-Mounted Accelerometers
3.5. Noseband-Mounted Accelerometers
3.6. Other Accelerometers-Related Sensors
4. Considerations around Sensor Choice
5. Future Considerations
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Accelerometer | Placement | Parameter | Measurement of Validity | NO. Animals |
---|---|---|---|---|
CowManager SensOor (Agis Automatisering BV, Harmelen, The Netherlands) | Ear (cow) | Percentage of eating time in 6 h recording | r = 0.88, κ = 0.77 [76] | 15 |
Percentage of eating time in about 20 h recording | r = 0.88, CCC = 0.99 [77] | 24 | ||
Percentage of ruminating time in 6 h recording | r = 0.93, κ = 0.85 [76] | 15 | ||
Percentage of eating time in about 20 h recording | r = 0.72, CCC = 0.99 [77] | 24 | ||
Percentage of eating/ruminating time in 40 h recording | r = 0.83 [78] | 10 | ||
Allflex® eSense™ (SCR Engineers Ltd., Netanya, Israel) | Ear (heifer) | Minute-level panting for 10 days | Se = 0.30–0.33, Sp > 0.70 [79] | 99 |
SMARTBOW (Smartbow GmbH, Weibern, Austria) | Ear (cow) | Hourly rumination time in 4 h recording | r= 0.97, CCC = 0.96 [80] | 48 |
Hourly rumination time in 20 h recording | r > 0.99 [81] | 10 | ||
Ear (calf) | Total ruminating time in 4 h recording | Se = 89.4%, Sp = 94.9%, Acc = 93.9%, Pr = 78.5%, F1 score = 83.6%, Kappa = 0.80 [82] | 15 | |
Total time of postures (lying, standing, locomotion) in 4 h recording | Se = 94.4%, Sp = 94.3%, Pr = 95.8%, Acc = 94.3% [82] | |||
HOBO Pendant G data loggers (Onset Computer Corporation, Pocasset, MA, USA) | Ear (cow) | Grazing time in 30 min recording | Se = 85.47%, Sp = 82.08%, Pr = 77.63% for the intervals of 5 min [67] | 20 |
Jaw (cow) | Grazing time in 30 min recording | R2 = 0.96 [83] | 7 | |
Rumination time in 30 min recording | R2 = 0.91 [83] | |||
Neck (cow) | Feeding time in 3 h recording | Se = 0.789, Sp = 0.937, R2 = 0.90 [84] | 12 | |
Leg (ewe and ram) | Walking, trotting and galloping duration in 15 min recording | Overall Acc = 87% [85] | 13 | |
Standing and lying duration in 15 min recording | Acc = 99.95% and 99.50%, respectively [85] | |||
GCDC X16-mini MEMS accelerometers (Gulf Coast Data Concepts, Waveland, MS, USA) | Ear (ewe) | Total grazing, standing and walking number in 10 s epochs sampling | Acc = 94%, 96% and 99%, respectively [86] Se, Sp, Acc and Pr from 92% to 100% [86] | 10 |
DairyCheck system (BITSz engineering GmbH, Zwickau, Germany) | Jaw (cow) | Total feeding time in 311–422 min recording | r = 0.86, R2 = 0.74 [87] | 14 |
Total rumination time in 311–422 min recording | r = 0.87, R2 = 0.75 [87] | |||
AML prototype V1.0 (AerobTec, Bratislava, Slovakia) | Lower jaw (sheep) | Total grazing, lying, running, standing and walking at 3, 5, 10 s epochs sampling | Acc = 81.5–85.5% [88] | 10 |
ADXL335 (Analog Devices, One Technology Way, Norwood, MA, USA) | Lower jaw (ewe) | Total grazing duration in 675 min recording | Se = 96%, Sp = 97%, Pr = 95%, Acc = 96% [89] | 3 |
Total ruminating duration in 675 min recording | Se = 89%, Sp = 97%, Pr = 89%, Acc = 95% [89] | |||
Total resting duration in 675 min recording | Se = 93%, Sp = 95%, Pr = 94%, Acc = 94% [89] | |||
BEHARUM device (Analog Devices, One Technology Way, Wilmington, MA, USA) | Lower jaw (ewe) | Grazing acceleration values per min for 20-25 min in the 30 s epoch sampling | Se = 94.8%, Sp = 93.0%, Pr = 94.1%, Acc = 94.0%, κ = 0.9 [90] | 48 |
Ruminating acceleration values per min for 20-25 min in the 30 s epoch sampling | Se = 80.4%, Sp = 94.7%, Pr = 88.1%, Acc = 90.0%, κ = 0.8 [90] | |||
Hr-Tag (Allflex SCR Engineers Ltd., Netanya, Israel) | Neck (cow) | Rumination times per 2 h recording | r = 0.93, R2 = 0.87 [91] | 27 |
Actiwatch Mini® (CamNtech, Cambridge, UK) | Neck (ewe) | Total counts of high, medium and low activity per min in 20 min sampling | Overall Acc = 79.98% for high/medium activity and 74.56% for low activity [92] | 9 |
Bosch BMI160 (Bosch-sensortec, Reutlingen, Germany) | Neck (sheep) | Grazing behavior points in 2 h recording with a window discretization | Sp = 98%, Pr = 96%, F-score = 95% [75] | 6 |
Ruminating behavior points in 2 h recording with a window discretization | Sp = 97%, Pr = 92%, F-score = 89% [75] | |||
MooMonitor+ (Dairymaster, Co. Kerry, Ireland) | Neck (cow) | Total feeding time in 4 h recording | r = 0.93, R2 = 0.85, CCC = 0.80 [93] | 24 |
Total ruminating time in 4 h recording | r = 0.99, R2 = 0.97, CCC = 0.95 [93] | |||
Total resting time in 4 h recording | r = 0.94, R2 = 0.88, CCC = 0.82 [93] | |||
Hourly grazing time in daily 4 h recording | r = 0.94, CCC = 0.97 [94] | 12 | ||
Hourly ruminating time in daily 4 h recording | r = 0.97, CCC = 0.98 [94] | |||
Omnisense Series 500 Cluster Geolocation System (Omnisense Ltd., Elsworth, UK) | Neck (cow) | Feeding bouts, feeding bout duration, and total feeding time (daily, morning/afternoon/night) | Sp = 93.0%, Pr = 83.5%, Acc = 83.2% [95] | 19 |
Total feeding duration in 36 h recording | Se = 98.78%, Pr = 93.10% [96] | 6 | ||
ADXL330 (Analog Devices, Norwood, MA 02062, USA) | Neck (cow) | Total feeding duration during 30 d | Se = 75%, Pr = 81%, Acc = 96% [97] | 30 |
Total ruminating duration during 30 d | Se = 75%, Pr = 86%, Acc = 92% [97] | |||
Axivity AX3 (Axivity Ltd., Newcastle, UK) | Neck (cow) | Minute-level feeding/rumination in 6 h recording | Overall Acc = 93% [98] | 10 |
Ear (ewe) | Total number of grazing behavior at 10 s epoch Support Vector Machine test | Acc = 76.9%, Se = 90.3%, Sp = 98.1%, Pr = 96.8%, κ = 0.6 [99] | 12 | |
Total number of active or inactive behaviors at 30 s epoch Classification and Regression Tree test | Acc = 98.1%, Se, Sp, Pr from 96.9% to 98.6%, κ = 1.0 [99] | |||
H30CD (Hitachi Metals, Ltd., Tokyo, Japan) | Neck (cow) | Minute-level eating, ruminating, lying in 6 h recording | Pr = 99.2% by a 10-fold cross-validation, Se = 100%, Sp = 100% [100] | 38 |
Kenz Lifecorder Plus device (LCP, Suzuken Co., Ltd., Nagoya, Japan) | Neck (cow) | Minute-level grazing in daily 4 h recording for 12 d | R2 = from 0.97 to 0.99 [101] | 6 |
GENEActiv (Activinsights Ltd., Kimbolton, Cambridgeshire, UK) | Neck (ewe and lamb) | Data points of standing and lying in ewes for 39 d | Average Acc = 83.7% [102] | 116 |
Data points of standing and lying in lambs for 39 d | Average Acc = 85.9% [102] | |||
Data points of activities in ewes for 39 d | Average Acc = 70.9% [102] | |||
Data points of activities in lambs for 39 d | Average Acc = 80.8% [102] | |||
ActiGraph wGT3X-BT® (ActiGraph, LLC, Pensacola, FL, USA) | Neck (lamb) | 5s epoch counts of grazing during 4 d recording | Acc = 91%, Se = 94%, Sp = 88%, Pr = 86% [103] | 6 |
5s epoch counts of resting during 4 d recording | Acc = 93%, Se = 89%, Sp = 96%, Pr = 96% [103] | |||
5s epoch counts of walking during 4 d recording | Acc = 95%, Se = 72%, Sp = 97%, Pr = 76% [103] | |||
InvenSense MPU-9250 (no mentioned provider) | Neck (lamb) | Confusion matrix for grazing activity in 22.5 h recording at the 5 s, 10 s and 15s epoch | Pr, Sp, Se, Acc between 92.6% to 98.9% [104] | 3 |
Track A Cow (ENGS, Rosh Pina, Israel) | Leg (cow) | Minute-level feeding time in 4 h recording per day | r = 0.93; CCC = 0.79 [80] | 48 |
Minute-level lying time in daily 4 h recording | r > 0.99; CCC > 0.99 [80] | |||
ADXL345 (Analog Devices, Norwood, MA 02062, USA) | Leg (cow) | Feeding duration at second-level window | Se = 52%, Pr = 55%, Acc = 80% [105] | 5 |
Active walking duration at second-level window | Se = 94%; Pr = 89%; Acc = 99% [105] | |||
Lying duration at second-level window | Se = 93%; Pr = 82%; Acc = 92% [105] | |||
Standing up duration at second-level window | Se = 74%; Pr = 85%; Acc = 99% [105] | |||
AfiAct Pedometer Plus (Afimilk, Kibbutz Afikim, Israel) | Leg (cow) | Hourly lying time in 4 h recording | r > 0.99; CCC > 0.99 [80] | 48 |
IceQube (IceRobotics Ltd., Edinburgh, Scotland) | Leg (cow) | Hourly lying time in 4 h recording | r > 0.99; CCC > 0.99 [80] | 48 |
Leg (lamb) | Second-level durations of standing, lying in daily 1 h recording for 40 h | Positive predictive value > 92%, sensitivity > 88% [106] | 10 | |
IceTag3D-accelerometer (IceRobotics Ltd., Edinburgh, UK) | Leg (lamb) | Second-level durations of standing, lying in daily 1 h recording for 40 h | Sensitivity and specificity > 91.5% [106] | 10 |
Second-level lying bouts in daily 1 h recording for 40 h | Positive predictive value > 44%, sensitivity > 91% [106] | |||
FEDO (ENGS, Rosh Pina, Israel) | Leg (calf) | Daily step counts, the number of lying bouts, lying time, the visits to feed bunk | Se = 68.8%, Sp = 72.4%, Acc = 71.5% [107] | 325 |
RumiWatch system (ITIN + HOCH GmbH, Liestal, Switzerland) | Noseband (beef cattle) | Hourly feeding time at 10 min interval sampling in daily 6 h recording for 6 d | Pr = 88%, Acc = 89%, r = 0.81 [108] | 8 |
Hourly rumination time at 10 min interval sampling in daily 6 h recording for 6 d | Pr = 76%, Acc = 91%, r = 0.75 [108] | |||
Leg (cow) | Lying duration over 24 h recording | r = 1 [109] | 18 | |
Standing and walking time over 10 min recording | r = 0.96 [109] | 21 |
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Fan, B.; Bryant, R.; Greer, A. Behavioral Fingerprinting: Acceleration Sensors for Identifying Changes in Livestock Health. J 2022, 5, 435-454. https://doi.org/10.3390/j5040030
Fan B, Bryant R, Greer A. Behavioral Fingerprinting: Acceleration Sensors for Identifying Changes in Livestock Health. J. 2022; 5(4):435-454. https://doi.org/10.3390/j5040030
Chicago/Turabian StyleFan, Bowen, Racheal Bryant, and Andrew Greer. 2022. "Behavioral Fingerprinting: Acceleration Sensors for Identifying Changes in Livestock Health" J 5, no. 4: 435-454. https://doi.org/10.3390/j5040030