Bachelor Abstract ID#1281 Bachelor Candidate Jared Lowe Advisin
Undergraduate Category: Engineering and Technology Degree Level: Bachelor Abstract ID#1281
Bachelor Candidate Jared Lowe Advising Committee: Behnaz Rezaei, Jason Yee, Sarah Ostadadabbas (PI)
Non-Contact Automatic Respiratory Monitoring in Restrained Voles Abstract
Methodology
Social behavior investigation in prairie voles can provide us with a valuable psychological model to understand social and emotional functions in both animals and humans. There have been several studies associated with respiratory pattern of these species in the state of fear-induced defense. However, non-invasive measurement methods employed so far suffer from the lack of creating a natural environment for the rodents. We present a remote depth-based system to extract respiration patterns. Our system estimates the breathing rate with the accuracy of 94.8% in comparison to visual inspection. Finally, we monitored the respiration of three voles in transition from a baseline to a fearful and back to a normal state, which the estimated breathing rates confirmed the existing animal defense strategy hypothesis.
Calibration:
Automatic breathing rate extraction algorithm: • Background Removal • Region of Interest (ROI) Extraction • Windowing • Normalized Autocorrelation • Breathing Rate Extraction • Averaging over ROI Pixels
Background
Taken from: http://www.vocalook.com/articles/learning-about-love-from-prairievole-bonding/
Conclusion Vole #3 validates our hypothesis. Its baseline restrained breathing shows a higher than average breathing rate due to being restrained. Its breathing decreases to 200bpm when the predator odor is introduced. This essentially immobilizes the animal, except for breathing, in a defense mechanism called “distal defense.” After the odor is removed, the breathing rate increases but is still below the initial baseline.
In order to translate the depth pixel intensity to a distance measurement unit, a calibration process was performed using a box with known dimensions placed in front of the camera in different distances from 50cm to 200cm, in 5cm increments.
Automatic breathing rate extraction algorithm
• Respiratory functioning is a central indicator of animal’s/human affective status [1]. • Among various laboratory animals, prairie voles’ social behavior is the most analogous to that exists between human [2].
Experimental Setup
Future Work • 1 minute to baseline the breathing in restraint • 1 minute of the vole exposed to the predator odor (mountain lion urine) • 1 minute of the odor removed with breathing in restraint
Experimental Results Preliminary Test: Human Subject Three minute periods of breathing were recorded at 10 cm increments between 80cm and 120cm. Breath count was visually recorded by both the participant and examiner as ground truth. The algorithm was applied to the depth data to extract the breathing rate. The average breathing rate of the subject was 16 bpm. The system was 100% accurate on extracting breathing rate from humans.
Our ultimate vision is to incorporate a motion tracking feature into the system to monitor the voles activity level in a freely moving caged environment. Vole tracking would integrate the Kinect’s RGB sensors to find the center of mass of the vole to plot location or distance traveled over time. When the vole is in low activity state, the system would switch to respiration monitoring to detect breathing rate. Object orientation and target acquisition would automate the region of interest selection. Eventually, we would like our system to automatically track multiple voles.
• The system was 94.8% accurate in extracting breathing rate from restrained voles as compared to visual inspection. • The average baseline was at 262 bpm.
Current Practice: • Current non-invasive methods for rodent respiration monitoring include whole body plethysmography and piezoelectric respirometry [3][4]. • Recently, non-contact respiratory monitoring based on the Microsoft Kinect depth sensing has been proposed to study respiration in humans.
• Three voles were then tested through the experiment procedure.
Acknowledgements This work was supported and conducted at the Augmented Cognition (AC) lab, Northeastern Electrical and Computer Engineering Department, under the supervision of Prof. Sarah Ostadabbas. H. Hoymann, "Lung Function Measurements in Rodents in Safety Pharmacology Studies", Frontiers in Pharmacology, vol. 3, 2012
http://www.i4sa.com/web_app/main/defaultProduct.asp x?ID=36&PT=3
A special thank goes to Dr. Jason Yee in the College of Science’s Department of Psychology. He and the Center for Translational Neuroimaging at Northeastern were the experts that helped us handle and understand the voles.
Objective We aim to verify the following hypothesis by applying a series of signal processing algorithms on the data collected from a depth-based sensing technology to monitor the respiration pattern in voles.
Hypothesis: • In Restraint: Higher induced baseline respiratory rate than a freely moving vole. • Predator Odor: Lower respiratory rate due to a shutdown of physiological systems. • Post Exposure/Stimulus Removal: Heightened rate after the odor is removed when the vole’s physiological response switches away from the fear stimulus and engage in a flight response
• Vole #3 has distinct staged responses to the different states. • Voles #2 and #4 show differing results. Vole #2 shows an increase after the odor is removed, while Vole #4 shows a decrease after the odor is introduced.
Another thank goes to Behnaz Rezaei, a graduate student from AC lab. While also working on her PhD with this project, Behnaz has helped me to better understand signal processing and the graduate research world. AC lab has been very helpful in creating a passionate team for this project and guiding me with my undergraduate research. References: [1] Carnevali, L., et al. “Respiratory patterns reflect different levels of aggressiveness and emotionality in Wild-type Groningen rats.” Respiratory Physiology and Neurobiology, 204, 28– 359 (2014). [2] S. Muroy, K. Long, D. Kaufer and E. Kirby, "Moderate Stress-Induced Social Bonding and Oxytocin Signaling are Disrupted by Predator Odor in Male Rats", Neuropsychopharmacology, 2016. [3] H. Hoymann, "Lung Function Measurements in Rodents in Safety Pharmacology Studies", Frontiers in Pharmacology, vol. 3, 2012. [4] D. Wilson and R. Sullivan, "Respiratory Airflow Pattern at the Rat’s Snout and a Hypothesis Regarding Its Role in Olfaction", Physiology & Behavior, vol. 66, no. 1, pp. 41-44, 1999.
Bachelor Candidate Jared Lowe Advising Committee: Behnaz Rezaei, Jason Yee, Sarah Ostadadabbas (PI)
Non-Contact Automatic Respiratory Monitoring in Restrained Voles Abstract
Methodology
Social behavior investigation in prairie voles can provide us with a valuable psychological model to understand social and emotional functions in both animals and humans. There have been several studies associated with respiratory pattern of these species in the state of fear-induced defense. However, non-invasive measurement methods employed so far suffer from the lack of creating a natural environment for the rodents. We present a remote depth-based system to extract respiration patterns. Our system estimates the breathing rate with the accuracy of 94.8% in comparison to visual inspection. Finally, we monitored the respiration of three voles in transition from a baseline to a fearful and back to a normal state, which the estimated breathing rates confirmed the existing animal defense strategy hypothesis.
Calibration:
Automatic breathing rate extraction algorithm: • Background Removal • Region of Interest (ROI) Extraction • Windowing • Normalized Autocorrelation • Breathing Rate Extraction • Averaging over ROI Pixels
Background
Taken from: http://www.vocalook.com/articles/learning-about-love-from-prairievole-bonding/
Conclusion Vole #3 validates our hypothesis. Its baseline restrained breathing shows a higher than average breathing rate due to being restrained. Its breathing decreases to 200bpm when the predator odor is introduced. This essentially immobilizes the animal, except for breathing, in a defense mechanism called “distal defense.” After the odor is removed, the breathing rate increases but is still below the initial baseline.
In order to translate the depth pixel intensity to a distance measurement unit, a calibration process was performed using a box with known dimensions placed in front of the camera in different distances from 50cm to 200cm, in 5cm increments.
Automatic breathing rate extraction algorithm
• Respiratory functioning is a central indicator of animal’s/human affective status [1]. • Among various laboratory animals, prairie voles’ social behavior is the most analogous to that exists between human [2].
Experimental Setup
Future Work • 1 minute to baseline the breathing in restraint • 1 minute of the vole exposed to the predator odor (mountain lion urine) • 1 minute of the odor removed with breathing in restraint
Experimental Results Preliminary Test: Human Subject Three minute periods of breathing were recorded at 10 cm increments between 80cm and 120cm. Breath count was visually recorded by both the participant and examiner as ground truth. The algorithm was applied to the depth data to extract the breathing rate. The average breathing rate of the subject was 16 bpm. The system was 100% accurate on extracting breathing rate from humans.
Our ultimate vision is to incorporate a motion tracking feature into the system to monitor the voles activity level in a freely moving caged environment. Vole tracking would integrate the Kinect’s RGB sensors to find the center of mass of the vole to plot location or distance traveled over time. When the vole is in low activity state, the system would switch to respiration monitoring to detect breathing rate. Object orientation and target acquisition would automate the region of interest selection. Eventually, we would like our system to automatically track multiple voles.
• The system was 94.8% accurate in extracting breathing rate from restrained voles as compared to visual inspection. • The average baseline was at 262 bpm.
Current Practice: • Current non-invasive methods for rodent respiration monitoring include whole body plethysmography and piezoelectric respirometry [3][4]. • Recently, non-contact respiratory monitoring based on the Microsoft Kinect depth sensing has been proposed to study respiration in humans.
• Three voles were then tested through the experiment procedure.
Acknowledgements This work was supported and conducted at the Augmented Cognition (AC) lab, Northeastern Electrical and Computer Engineering Department, under the supervision of Prof. Sarah Ostadabbas. H. Hoymann, "Lung Function Measurements in Rodents in Safety Pharmacology Studies", Frontiers in Pharmacology, vol. 3, 2012
http://www.i4sa.com/web_app/main/defaultProduct.asp x?ID=36&PT=3
A special thank goes to Dr. Jason Yee in the College of Science’s Department of Psychology. He and the Center for Translational Neuroimaging at Northeastern were the experts that helped us handle and understand the voles.
Objective We aim to verify the following hypothesis by applying a series of signal processing algorithms on the data collected from a depth-based sensing technology to monitor the respiration pattern in voles.
Hypothesis: • In Restraint: Higher induced baseline respiratory rate than a freely moving vole. • Predator Odor: Lower respiratory rate due to a shutdown of physiological systems. • Post Exposure/Stimulus Removal: Heightened rate after the odor is removed when the vole’s physiological response switches away from the fear stimulus and engage in a flight response
• Vole #3 has distinct staged responses to the different states. • Voles #2 and #4 show differing results. Vole #2 shows an increase after the odor is removed, while Vole #4 shows a decrease after the odor is introduced.
Another thank goes to Behnaz Rezaei, a graduate student from AC lab. While also working on her PhD with this project, Behnaz has helped me to better understand signal processing and the graduate research world. AC lab has been very helpful in creating a passionate team for this project and guiding me with my undergraduate research. References: [1] Carnevali, L., et al. “Respiratory patterns reflect different levels of aggressiveness and emotionality in Wild-type Groningen rats.” Respiratory Physiology and Neurobiology, 204, 28– 359 (2014). [2] S. Muroy, K. Long, D. Kaufer and E. Kirby, "Moderate Stress-Induced Social Bonding and Oxytocin Signaling are Disrupted by Predator Odor in Male Rats", Neuropsychopharmacology, 2016. [3] H. Hoymann, "Lung Function Measurements in Rodents in Safety Pharmacology Studies", Frontiers in Pharmacology, vol. 3, 2012. [4] D. Wilson and R. Sullivan, "Respiratory Airflow Pattern at the Rat’s Snout and a Hypothesis Regarding Its Role in Olfaction", Physiology & Behavior, vol. 66, no. 1, pp. 41-44, 1999.
