Search Results (20)

Human remains detection (HRD) dogs are vital tools in forensic science and disaster response, but their training is limited by the restricted availability of human material. Synthetic odorants such as Sigma Pseudo™ formulations provide safer, standardized alternatives, yet current products reproduce only a fraction of the volatile organic compound (VOC) profile of decomposition. In particular, sulfur-containing volatiles, which are highly odor-active and consistently present in human remains, are often missing, reducing biological fidelity. Here, we integrate analytical chemistry with canine olfactory genetics and molecular biology to explain these limitations. Dogs possess one of the largest olfactory receptor (OR) repertoires among mammals, with high allelic diversity and specialized trace amine-associated receptors (TAARs) tuned to cadaveric amines. Together with olfactory binding proteins (OBPs) and ciliary signal transduction cascades, these molecular mechanisms highlight why incomplete VOC mixtures may fail to activate the full receptor network required for reliable odor imprinting. We propose the “sulfur gap hypothesis” and suggest hybrid training strategies combining improved synthetics with ethically sourced biological samples to enhance HRD dog performance. Full article

The detection of blood by human remains detection (HRD) canines and blood detection dogs (BDDs) is crucial to both search and rescue (SAR) and crime scene investigation. They can be used to find both missing persons and to detect otherwise undetectable blood evidence at crime scenes. An added level of difficulty with training occurs as blood volatile organic compounds (VOCs) are drastically affected by time. Previous studies have shown this, with a focus on a longer timescale (weeks/months). Little data exists on the changes in the first 48 h, the most crucial time in SAR, something this study aims to rectify. Data was collected using headspace solid-phase microextraction/gas chromatography–mass spectrometry, which was then analyzed using chemometrics and confirmed with canine trials. The results of the laboratory analysis indicated that there were multiple, distinct odor profiles between the 1 h and 2-week time windows—namely, the fresh, intermediate, and aged stages of decomposition. The noted changes in the odor profiles were validated with HRD canine trials. Canines had difficulty detecting the fresh blood (1–2 h old) and had the greatest detection rate for the aged blood (34–36 h old). Both the chemical analysis and canine behavior data displayed a clear change in the odor profile within the first 48 h. This information will assist SAR, HRD, and BBD training to ensure they train on all distinct odor profiles. Full article

Mammary tumours are the most common neoplasia in adult female dogs. Mastectomy leads to moderate to severe pain. Effective pain management is crucial in veterinary medicine. This review outlines analgesic techniques for managing perioperative pain in dogs undergoing mastectomy. A literature search on dog mastectomy analgesia was conducted from January 2001 to January 2025. Pre-emptive meloxicam reduces postoperative cardiovascular changes without affecting renal function. When combined with gabapentin, it lowers the need for rescue analgesic opioids, similar to robenacoxib. With regard to tramadol, it offers contrasting analgesia in the studies considered when used alone, while its effect appears enhanced when used in combination with meloxicam/dipyrone. However, methadone provides superior pain control, especially when given preoperatively or intraoperatively. The combination of ketamine, lidocaine, and maropitant enhances pain management, while fentanyl, alone or with lidocaine and ketamine, is effective for intraoperative pain control. Local infiltration with lidocaine/bupivacaine provides effective pain control, and devices like Comfont-in^® or WSC facilitate this process. Tumescent anaesthesia using lidocaine/ropivacaine allows for extensive infiltration of the mammary gland. Epidural analgesia, paravertebral blocks, and TAP blocks are beneficial in multimodal protocols. Transdermal patches containing fentanyl/buprenorphine offer prolonged analgesia, while electroacupuncture can help reduce the need for rescue analgesics. Multimodal analgesic protocols are crucial for effective pain management in dog mastectomy surgeries, minimising the need for rescue opioids. Full article

The aim of this study was to observe electric cardiac activity in real working conditions, with the application of Holter and the electrocardiogram in search and rescue dogs. Thirty-one handlers of search and rescue dogs voluntarily participated in this study. Nine dogs were selected to wear the Holter, and twenty-three were submitted to electrocardiographic recordings (one dog, excluded by Holter examination, was then included in the ECG group). Our results showed few cardiac rhythm alterations, such as escape beats, premature ventricular beat, and depression and elevation of the ST segment, particularly during the working phase in the Holter group and during recovery time immediately after activity in the electrocardiographic group. Detected alterations in real working conditions may provide more information than routine checks, and Holter monitoring can be more functional. However, not all dogs tolerate wearing the Holter harness, and more time is thus needed to apply the equipment. In addition, the results are not immediate, and the absence of water is essential because it would damage the equipment. Full article

Dogs’ (Canis lupus familiaris) sense of smell is based on a unique anatomy and physiology that enables them to find and differentiate low concentrations of odor molecules. This ability is exploited when dogs are trained as search, rescue, or medical detection dogs. We performed a three-part study to explore the scent detection threshold of 15 dogs to an in-house-made Eucalyptus hydrolat. Here, decreasing concentrations of the hydrolat were tested using a three-alternative forced-choice method until the first incorrect response, which defined the limit of scent detection for each tested dog. Quantitative proton nuclear magnetic resonance spectroscopy was used to identify and measure the contents of ten commercial Eucalyptus hydrolats, which are used in a dog scent training sport called “nose work”. In this study, the dogs’ limit of detection initially ranged from 1:10⁴ to 1:10²³ but narrowed down to 1:10¹⁷–1:10²¹ after a training period. The results show that, with training, dogs learn to discriminate decreasing concentrations of a target scent, and that dogs can discriminate Eucalyptus hydrolat at very low concentrations. We also detected different concentrations of eucalyptol and lower alcohols in the hydrolat products and highlight the importance of using an identical source of a scent in training a dog for participation in canine scent sport competitions and in olfactory research. Full article

Understanding the VOC profile released during the early post-mortem period is essential for applications in training human remains detection dogs and urban search and rescue operations (USAR) to rapidly locate living and deceased victims. Human cadavers were sampled at the UQTR morgue within a 0–72 h post-mortem interval. VOC samples were collected from the headspace above the cadavers, using Tenax TA/Carbograph 5TD dual sorbent tubes, and analyzed using GC×GC-TOFMS. Multiple data processing steps, including peak table alignment and filtering, were undertaken using LECO ChromaToF and custom scripts in R programming language. This study identified 104 prevalent VOCs, some of which are linked to human decomposition, while others are connected to the persistence of living scent. Principal Component Analysis (PCA) further highlighted that VOC profiles can change dynamically over time, even in a controlled setting. The findings underscore the complexity and variability in VOC profiles during the early post-mortem period. This variability is influenced by multiple factors including the individual’s biological and physiological conditions. Despite the challenges in characterizing these profiles, the identified VOCs could potentially serve as markers in forensic applications. The study also highlights the need for additional research to build a dataset of VOCs for more robust forensic applications. Full article

Robots with bio-inspired locomotion systems, such as quadruped robots, have recently attracted significant scientific interest, especially those designed to tackle missions in unstructured terrains, such as search-and-rescue robotics. On the other hand, artificial intelligence systems have allowed for the improvement and adaptation of the locomotion capabilities of these robots based on specific terrains, imitating the natural behavior of quadruped animals. The main contribution of this work is a method to adjust adaptive gait patterns to overcome unstructured terrains using the ARTU-R (A1 Rescue Task UPM Robot) quadruped robot based on a central pattern generator (CPG), and the automatic identification of terrain and characterization of its obstacles (number, size, position and superability analysis) through convolutional neural networks for pattern regulation. To develop this method, a study of dog gait patterns was carried out, with validation and adjustment through simulation on the robot model in ROS-Gazebo and subsequent transfer to the real robot. Outdoor tests were carried out to evaluate and validate the efficiency of the proposed method in terms of its percentage of success in overcoming stretches of unstructured terrains, as well as the kinematic and dynamic variables of the robot. The main results show that the proposed method has an efficiency of over 93% for terrain characterization (identification of terrain, segmentation and obstacle characterization) and over 91% success in overcoming unstructured terrains. This work was also compared against main developments in state-of-the-art and benchmark models. Full article

A survey with 100 multiple choice and open-ended questions was proposed by free access to working dogs’ handlers. One hundred and nine respondents were recorded and their dates processed. The most represented breeds were: Belgian Malinois, Labrador, Border Collie and German Shepherds. Of these, 71.6% were intact dogs and 28.4% were spayed or neutered, with a median age range of 3–4 years. Furthermore, 55.5% had undergone early radiographic examinations for hip or elbow dysplasia diagnosis. The dogs performed the following activities: search and rescue on surface (59%), search and rescue on rubble (37%), Internationale Gebrauchshund Pruefung (IGP) (9%), man trailing (5%), sled dog (5%), search on avalanche (4%), dog towing (3%), canine shows (3%), hunting (2%), water rescue (1%), pet therapy (1%), wildlife conservation dog (1%), Mondioring (1%). Only 36.4% of respondents submitted their dogs to a specific sports medical examination and 55.5% to an orthopaedic examination. An injury incidence of 45.5% was recorded, generally related to mild musculoskeletal trauma. A limited number of handlers routinely performed warm-up and/or cool-down activities. A positive assessment emerged of the need for many respondents to attend and request education courses and updates on the proper health management of their dogs. Full article

Cell-free miRNAs, called circulating miRNAs (cmiRNAs), can act in a paracrine manner by facilitating a diversity of signaling mechanisms between cells. Real-time qPCR is the most accepted method for quantifying miRNA expression levels. The use of stable miRNA endogenous control (EC) for qPCR data normalization allows an accurate cross-sample gene expression comparison. The appropriate selection of EC is a crucial step because qPCR data can change drastically when normalization is performed using an unstable versus a stable EC. To find EC cmiRNA with stable expression in search and rescue (SAR) working dogs, we explored the serum miRNome by Next-Generation Sequencing (NGS) at T0 (resting state) and T1 immediately after SAR performance (state of physiologically recovered stress). The cmiRNAs selected in the NGS circulating miRNome as probable ECs were validated by qPCR, and miRNA stability was evaluated using the Delta Ct, BestKeeper, NormFinder, and GeNorm algorithms. Finally, RefFinder was used to rank the stability orders at both T0 and T1 by establishing miR-320 and miR-191 as the best-circulating ECs. We are confident that this study not only provides a helpful result in itself but also an experimental design for selecting the best endogenous controls to normalize gene expression for genes beyond circulating miRNAs. Full article

This paper presents a system for behavioral, environmental, and physiological monitoring of working dogs using on-body and aerial sensors. The proof of concept study presented here includes two trained dogs performing nine scent detection tasks in an uncontrolled environment encompassing approximately two acres. The dogs were outfitted with a custom designed wearable harness to monitor their heart rate, activity levels and skin temperature. We utilized a commercially available micro-air vehicle to perform aerial sensing by tracking the terrain and movement of the dog in the outdoor space. The dogs were free to explore the space working at maximal speeds to complete a scent-based search-and-retrieval task. Throughout the experiment, the harness data was transferred to a base station via Wi-Fi in real-time. In this work, we also focused on testing the performance of a custom 3D electrode with application specific ergonomic improvements and adaptive filter processing techniques to recover as much electrocardiography data as possible during high intensity motion activity. We were able to recover and use 84% of the collected data where we observed a trend of heart rate generally increasing immediately after successful target localization. For tracking the dogs in the aerial video footage, we applied a state-of-the-art deep learning algorithm designed for online object tracking. Both qualitative and quantitative tracking results are very promising. This study presents an initial effort towards deployment of on-body and aerial sensors to monitor the working dogs and their environments during scent detection and search and rescue tasks in order to ensure their welfare, enable novel dog-machine interfaces, and allow for higher success rate of remote and automated task performance. Full article

Search and Rescue (SaR) dogs are important assets in the hands of first responders, as they have the ability to locate the victim even in cases where the vision and or the sound is limited, due to their inherent talents in olfactory and auditory senses. In this work, we propose a deep-learning-assisted implementation incorporating a wearable device, a base station, a mobile application, and a cloud-based infrastructure that can first monitor in real-time the activity, the audio signals, and the location of a SaR dog, and second, recognize and alert the rescuing team whenever the SaR dog spots a victim. For this purpose, we employed deep Convolutional Neural Networks (CNN) both for the activity recognition and the sound classification, which are trained using data from inertial sensors, such as 3-axial accelerometer and gyroscope and from the wearable’s microphone, respectively. The developed deep learning models were deployed on the wearable device, while the overall proposed implementation was validated in two discrete search and rescue scenarios, managing to successfully spot the victim (i.e., obtained F1-score more than 99%) and inform the rescue team in real-time for both scenarios. Full article

This study aimed to assess the heart rate (HR) responses of avalanche SAR dogs and handlers under working field conditions. Thirteen SAR units (dogs and handlers) performed an exercise (Endurance) consisting of approximately 5.5 km of rough tracks through deep snow, at an altitude of 1991–2250 m.a.s.l. The exercise was repeated twice for each of the two different tracks. Both handlers and dogs were equipped with a global positioning satellite/heart rate (GPS/HR) system (Polar^®). Multivariable models were used to evaluate the effects of environmental (i.e., gradient, altitude, track, and time) and intrinsic (i.e., speed, repetition, and breed) factors on changes from baseline HR (Δ%HR). The dog’s Δ%HR was greater in the flat and uphill compared with downhill, and increased progressively as the speed increased (p < 0.001). Moreover, it rose at altitudes above 2100 m.a.s.l. and peaked after 30 min of the Endurance activity (p < 0.01). These findings indicated that HR monitors could be a valuable tool to contribute to the evaluation of avalanche dogs’ fitness in their real working environment. In contrast, the lack of correlation between the dogs’ and handlers’ HR changes suggests that handlers might not perceive the physical conditions of their dog in real-time. Thus, implementing protocols to monitor avalanche SAR dogs’ fitness using a GPS/HR monitoring system could help handlers to tailor the training and workload and to detect the risk factors for physical distress of working dogs. Full article

Technological breakthroughs in recent years have led to a revolution in fields such as Machine Vision and Search and Rescue Robotics (SAR), thanks to the application and development of new and improved neural networks to vision models together with modern optical sensors that incorporate thermal cameras, capable of capturing data in post-disaster environments (PDE) with rustic conditions (low luminosity, suspended particles, obstructive materials). Due to the high risk posed by PDE because of the potential collapse of structures, electrical hazards, gas leakage, etc., primary intervention tasks such as victim identification are carried out by robotic teams, provided with specific sensors such as thermal, RGB cameras, and laser. The application of Convolutional Neural Networks (CNN) to computer vision is a breakthrough for detection algorithms. Conventional methods for victim identification in these environments use RGB image processing or trained dogs, but detection with RGB images is inefficient in the absence of light or presence of debris; on the other hand, developments with thermal images are limited to the field of surveillance. This paper’s main contribution focuses on implementing a novel automatic method based on thermal image processing and CNN for victim identification in PDE, using a Robotic System that uses a quadruped robot for data capture and transmission to the central station. The robot’s automatic data processing and control have been carried out through Robot Operating System (ROS). Several tests have been carried out in different environments to validate the proposed method, recreating PDE with varying conditions of light, from which the datasets have been generated for the training of three neural network models (Fast R-CNN, SSD, and YOLO). The method’s efficiency has been tested against another method based on CNN and RGB images for the same task showing greater effectiveness in PDE main results show that the proposed method has an efficiency greater than 90%. Full article

Epilepsy is a debilitating and potentially life-threatening neurological condition which affects approximately 65 million people worldwide. There is currently no reliable and simple early warning seizure-onset device available, which means many people with unstable epilepsy live in fear of injury or sudden death and the negative impact of social stigmatization. If anecdotal claims that untrained dogs anticipate seizures are found to be true, they could offer a simple and readily available early warning system. We hypothesized that, given the extraordinary olfactory ability of dogs, a volatile organic compound exhaled by the dog’s epileptic owner may constitute an early warning trigger mechanism to which make dogs react by owner-directed affiliative responses in the pre-seizure period. Using 19 pet dogs with no experience of epilepsy, we exposed them to odours that were deemed to be characteristic of three seizure phases, by using sweat harvested from people with epilepsy. The odours were delivered to a point immediately under a non-epileptic and seated pet dog owner’s thighs. By altering the alternating odours emerging from sweat samples, captured before seizure, during a seizure and after a seizure, and two nonseizure controls, we were able to record the response of the 19 pet dogs. Our findings suggest that seizures are associated with an odour and that dogs detect this odour and demonstrate a marked increase in affiliative behaviour directed at their owners. A characteristic response of all 19 dogs to seizure odour presentation was an intense stare which was statistically significant, (p < 0.0029), across the pre-seizure, seizure and post-seizure phases when compared to control odours of nonseizure origin. Full article

The clinical profiles of muscle biomarkers (Creatine Kinase–CK-and Aspartate Aminotransferase–AST) performed during training may help in determining the fitness level of dogs and their potentiality to perform specific activities. This study investigated the potential variations of physiological parameters and muscular biomarkers in trained search and rescue dogs during search activity in two different areas. The aim was to verify the absence of any muscular enzymes after 20 min of search activity. The variations of physiological parameters (pulse rate; respiratory rate; rectal body temperature) and skeletal muscular biomarkers (CK and AST) were evaluated before and after search activity. Twenty-three trained dogs met the inclusion criteria and were divided into two groups. One group experienced search activity in a well-known area, while the second one in a similar, but unknown, area. The results for physiological parameters and skeletal muscular biomarkers values showed no significant differences between the two groups (p > 0.05), confirming that an effective conditioning protects against enzymatic alteration during a 20 min duration of submaximal activity. Full article