ABSTRACT
The healthy function of the vestibular system (VS) is of vital importance for individuals to carry out their daily activities independently and safely. This study carries out Tsallis entropy (TE)-based analysis on insole force sensor data in order to extract features to differentiate between healthy and VS-diseased individuals. Using a specifically developed algorithm, we detrend the acquired data to examine the fluctuation around the trend curve in order to consider the individual's walking habit and thus increase the accuracy in diagnosis. It is observed that the TE value increases for diseased people as an indicator of the problem of maintaining balance. As one of the main contributions of this study, in contrast to studies in the literature that focus on gait dynamics requiring extensive walking time, we directly process the instantaneous pressure values, enabling a significant reduction in the data acquisition period. The extracted feature set is then inputted into fundamental classification algorithms, with support vector machine (SVM) demonstrating the highest performance, achieving an average accuracy of 95%. This study constitutes a significant step in a larger project aiming to identify the specific VS disease together with its stage. The performance achieved in this study provides a strong motivation to further explore this topic.
ABSTRACT
OBJECTIVE: This study aimed to describe the type and number of traumatic injuries seen after devastating earthquakes and to evaluate the difficulties experienced in the treatment process in a primary affected center. METHODS: Out of the 2176 patients who were treated in the emergency department, 372 (199 male and 173 female) patients with complete data were included in this single-center retrospective study. In addition to the demographic characteristics of the patients, orthopedic injuries, other organ system injuries, type of injury, treatments, mechanisms of injury, and time of presentation to the emergency department were recorded. RESULTS: The most common age group for injury was 20-30 years old, consisting of 73 patients (19.62%), and the second most common age group was between 40 and 50, with 72 patients (19.35%). Injury after being trapped under rubble was seen in 152 (40.86%) patients, while non-debris causes were more common in 220 patients (59.14%). The most common site of injury was in the lower extremities, with 111 patients (29.84%), while multiple injuries were seen in 109 patients (29.3%). Lower extremity fractures were mostly seen in long bones such as the femur (12.28%) and tibia (11.4%). Upper extremity fractures, especially those due to falls, were most frequently in the distal radius (8.77%). After triage, 117 patients (31.45%) were hospitalized, whereas the majority of patients (58.33%) were discharged from the emergency department. CONCLUSION: This study has shown us that injuries following major earthquakes are of a wide spectrum and occur in large numbers and in a very short time. Even in a well-equipped hospital that is not affected by an earthquake, there are many barriers to appropriate management. The first 24 hours after an earthquake are critical. This period should be kept in mind while organizing and taking necessary precautions, and early responses to earthquakes should be meticulously planned.