SA104G Small Animal Energy Metabolism Monitoring System Introduction: The high-resolution small animal energy metabolism monitoring system and the multi reusable metabolism measurement system for small animals can synchronously measure energy consumption, respiratory entropy, VO2, VCO2, and animal activity. The perfect fusion of high-resolution and synchronized stereoscopic data acquisition. The digital platform of SANS's small animal energy metabolism monitoring system updates all the data captured by sensors in the cage at a rate of once per second, including the animal's position, food intake, cage movement, and body weight. This generates a rich data stream and raw data storage that meets GLP requirements, allowing users to conduct flexible analysis. characteristic: Energy consumption (EE) 1. The system uses gas concentration sensors imported from the UK to accurately measure oxygen and carbon dioxide concentrations, ranging from 5-100% oxygen; 0-10% carbon dioxide; The detection accuracy is 1PPM. Stability (4 hours): ± 0.3% O2 in XC mode; ± 0.1% in LN mode; 2. High precision flow control, using imported sensors from the United States to accurately control gas flow, with a control progress of 0-5L/min and a control accuracy of ± 0.001L/min; 3. Calculation: Using indirect calorimetry, calculate the energy consumption of animals based on the oxygen heat value corresponding to different respiratory entropies. Activity detection 1. The position tracking adopts deep classification model and position sensitive model algorithm to achieve high-speed and accurate tracking effect, with a detection accuracy of 1mm. The animal's movement amount is separately counted on the X, Y, and Z axes, and the total movement amount and sub axis movement amount can be calculated. The number of times the animal stands and the standing time can also be recorded. At the same time, it can be associated with energy consumption for display, revealing the relationship between animal movement and energy consumption. 2. The sensor accuracy is 1mm, which is higher than the precision of video tracking technology. 3. Location heatmap: The system depicts the probability heatmap of the location during the experimental process. Food and water intake testing 1. Real time monitoring through gravity sensors, accurate to 0.01g, software can filter out measurement inaccuracies caused by animals eating food; 2. Detection frequency 50Hz, response time 0.02 seconds; 3. Data recording: The software real-time depicts time-based detection of food and water intake, while correlating energy consumption curves. motion detection The running wheel module is used to record the movement distance and speed of animals, and can also be associated with energy consumption for display, revealing the relationship between animal movement and energy consumption; Speed detection: detection accuracy of 0.001 meters per second; Distance detection: detection accuracy of 0.001 meters. Fecal separation device 1. The equipment adopts abrasive production, with a fecal separation efficiency of over 95%; 2. The separation module can simultaneously detect parameters such as animal activity level, diet, and drinking water; 3. One machine with multiple functions, can be separated for energy metabolism and metabolism with fecal separation; 4. Removing the fecal separation module increases the flexibility of the experiment; 5. Refrigeration device: The system is equipped with a low-temperature storage module to reduce the volatilization of feces, which is beneficial for later use
Introduction: The high-resolution small animal energy metabolism monitoring system and the multi reusable metabolism measurement system for small animals can synchronously measure energy consumption, respiratory entropy, VO2, VCO2, and animal activity. The perfect fusion of high-resolution and synchronized stereoscopic data acquisition. The digital platform of SANS's small animal energy metabolism monitoring system updates all the data captured by sensors in the cage at a rate of once per second, including the animal's position, food intake, cage movement, and body weight. This generates a rich data stream and raw data storage that meets GLP requirements, allowing users to conduct flexible analysis.
