# Research Progress in the Early Warning of Chicken Diseases by Monitoring Clinical Symptoms
## 2 Early Diseases Detection through Physiological Characteristics
### Abnormal Body Temperature  
The chicken is a kind of homeothermic animal that produces and dissipates heat to maintain a relatively constant temperature, including core and skin surface temperature [50,51]. However, under pathological or stress conditions, the temperature will change due to infection or emergency response. So, the temperature can be an important physiological indicator for the early warning and detection of chicken diseases. Footpad dermatitis (FPD) is a condition that causes necrotic lesions on the plantar surface of the footpads in growing broilers, which is considered an animal welfare issue  
Figure 3: Sound time domain signals for four classes of chickens: healthy, infected Newcastle disease, bronchitis virus and avian influenza. Reprinted with permission from Ref. [43]. and could cause huge economic losses [52]. The dielectric constant (DC) value, which can be obtained by measuring the plantar skin of the footpads with a moisture-meter device consisting of an electronic control unit and a sensor probe, is useful in the diagnosis of FPD. [PERSON] et al. [53] found that the DC value would be decreased monotonically with increasing FPD score and the negative correlation between DC and FPD score was significant (\(p<0.0001\)). FPD is normally accompanied by a change in the temperature of the plantar surface of the foot and footpads. Plantar temperature measurements were carried out on eighty 10-week-old turkeys by using thermal imaging, and the results showed that footpad temperatures were significantly lower than foot temperatures under normal conditions and the severity of mild footpad dermatitis as scored visually was negatively associated with the temperatures of the plantar surface of the foot and footpads [54]. Furthermore, chickens could be classified into three categories (FPD negative, suspect and positive) according to the temperature change from the metatarsal footpad to the digit extremities [55]. By analyzing the plantar surface temperature of 150 randomly selected hens, it was found that the correlation between samples classified as positive by thermal images and clinical FPD visual score was 86.7%. The result indicates that thermal imaging represents a novel tool for the reliable and noninvasive early detection of foot pathologies, which is a more sensitive indicator of subclinical infection than the visual appraisal. In addition, [PERSON] et al. [56] demonstrated that thermal imaging can obtain the body surface temperature of poultry and identify healthy and sick chickens based on the temperature difference between their heads and legs. The head part of a chicken is a key region for obtaining body temperature information, and its correct identification is crucial. In addition to the algorithm optimization, the installation method of thermal infrared camera is also important. The study of [PERSON] et al. [57] showed that the thermal infrared images collected from 160 cm height and 30\({}^{\circ}\) pitch angle are better, and the recognition accuracy of the broiler head is 91.3%. For AI, researchers have focused on developing portable AI detection devices based on PCR and biosensor technology in recent years [22; 58; 59; 60]; however, these techniques are relatively expensive and require sophisticated personnel to operate. Consequently, a prototype wearable wireless node with a thermistor and an accelerometer to detect chickens infected with highly pathogenic AI was developed [61]. The results showed that the sudden decrease in body temperature of the infected chickens was detectable before chickens showed clinical signs and gross lesions. There are also studies that applied thermal imaging technology to AI detection. The maximum surface temperature of chickens would increase at least 24 h before the manifestation of clinical signs of AI infection, depending on the severity, which means the surface temperature of chickens could be considered an early indicator of AI [62].