Background: Femoroacetabular impingement syndrome (FAI) is a complex, often post-traumatically developing impairment of the hip joint. It is characterized by ambiguous symptomatology, which makes early diagnosis difficult. Aim: The study was conducted to evaluate the applicability of a triaxial gyroscopic sensor in routine practice as an additional indication criterion for operative versus conservative treatment procedures. Methods: Ninety-two patients were included in the experimental retrospective study and 62 completed the examination. All patients signed informed consent. A gyroscopic sensor was placed on the right side of the pelvis above the hip joint and patients walked approximately 15 steps. Data were also evaluated while the patients climbed stairs. A complete clinical examination of the dynamics and physiological movements in the joint was performed. The data measured by the gyroscopic sensor were processed using differential geometry methods and subsequently evaluated using spectral analysis and neural networks. Results: FAI diagnosis using gyroscopic measurement is fast and easy to implement. Our approach to processing the gyroscopic signals used to detect the stage of osteoarthritis and post-traumatic FAI could lead to more accurate detection and capture early in FAI development. Conclusions: The obtained data are easily evaluated, interpretable, and beneficial in the diagnosis of the early stages of FAI. The results of the study show that this approach can lead to more accurate and early detection of osteoarthritis and post-traumatic FAI.
- MeSH
- analýza chůze metody MeSH
- biomechanika * MeSH
- femoroacetabulární impingement * chirurgie diagnóza patofyziologie MeSH
- kyčelní kloub patofyziologie MeSH
- lidé MeSH
- nositelná elektronika * MeSH
- osteoartróza diagnóza patofyziologie MeSH
- retrospektivní studie MeSH
- telemedicína metody MeSH
- umělá inteligence MeSH
- Check Tag
- lidé MeSH
PURPOSE OF THE STUDY Femoroacetabular impingement syndrome is a complex, often post-traumatically developing impairment of the hip joint, characterized by ambiguous symptomatology, which makes early diagnosis diffi cult, especially in the early stages. Experimental retrospective study was carried out to evaluate the usability of a triaxial gyroscopic sensor in routine practice as an additional indication criterion for operative versus conservative treatment procedures. MATERIAL AND METHODS 92 patients were included in the retrospective study, and 62 completed the investigation. All patients signed informed consent. A gyroscopic sensor was placed on the right side of the pelvis above the hip joint, and the patients walked approximately 15 steps. Furthermore, an evaluation of the data during stair climbing and a complete clinical examination of the dynamics and physiological movements in the joint was carried out. Data measured with a gyroscopic sensor were processed using differential geometry methods and then evaluated using spectral analysis and neural networks. The proposed technique of diagnosing FAI using gyroscope measurement is a fast, easy-to-perform method. RESULTS Our approach in processing gyroscopic signals used to detect the stage of arthrosis and post-traumatically developing FAI could lead to more accurate early detection and capture in the early stages. CONCLUSIONS The obtained data are easily evaluated, interpretable and benefi cial in diagnosing the early stages of FAI. The results of the conducted research showed this approach to more accurate early detection of arthrosis and post-traumatically developing FAI. Key words: wearable sensors; osteoarthritis; mathematical biophysics; telemedicine.
Osteoarthritis is the most common type of degenerative joint disease and affects millions of people. In this paper, we propose a non-obtrusive and straightforward method to assess the progression of osteoarthritis. In standard medicine praxis, osteoarthritis is observed with X-rays. In this study, we use widely available wearable sensors with gyroscopes to make the observation. Two novel methods are proposed for gyroscope data processing. A small-scale study has shown that these methods can be used to monitor osteoarthritis's progression, and to differentiate between healthy subjects and subjects with femoroacetabular impingement syndrome.
- MeSH
- artroskopie metody MeSH
- artróza kyčelních kloubů * diagnostické zobrazování MeSH
- femoroacetabulární impingement * diagnostické zobrazování MeSH
- kyčelní kloub MeSH
- lidé MeSH
- osteoartróza * diagnostické zobrazování MeSH
- rentgendiagnostika MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Background and Objectives Automatic detection of breathing disorders plays an important role in the early signalization of respiratory diseases. Measuring methods can be based on electrocardiogram (ECG), sound, oximetry, or respiratory analysis. However, these approaches require devices placed on the human body or they are prone to disturbance by environmental influences. To solve these problems, we proposed a heart contraction mechanical trigger for unobtrusive detection of respiratory disorders from the mechanical measurement of cardiac contractions. We designed a novel method to calculate this mechanical trigger purely from measured mechanical signals without the use of ECG. Methods The approach is a built-on calculation of the so-called euclidean arc length from the signals. In comparison to previous researches, this system does not require any equipment attached to a person. This is achieved by locating the tensometers on the bed. Data from sensors are fused by the Cartan curvatures method to beat-to-beat vector input for the Convolutional neural network (CNN) classifier. Results In sum, 2281 disordered and 5130 normal breathing samples was collected for analysis. The experiments with use of 10-fold cross validation show that accuracy, sensitivity, and specificity reach values of 96.37%, 92.46%, and 98.11% respectively. Conclusions By the approach for detection, the system offers a novel way for a completely unobtrusive diagnosis of breathing-related health problems. The proposed solution can effectively be deployed in all clinical or home environments.
- MeSH
- algoritmy MeSH
- elektrokardiografie * MeSH
- lidé MeSH
- nemoci dýchací soustavy * MeSH
- neuronové sítě (počítačové) MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Background and Objectives: The mechanism of the relationship between glycemia and lipid metabolism has not been completely clarified, and slight differences may be found between authors and the kinds of evaluated parameters. Therefore, this study focused on possible changes of lipoprotein profile with regards to HOMA IR (Homeostatic Model Assessment for Insulin Resistance) cut-off 3.63, considered a signal of glucose metabolism alterations. Materials and Methods: The metabolic profiles of 3051 individuals were divided by HOMA IR values into two groups below cut-off 3.63, including (n = 2627) and above cut-off (n = 424). Patients taking medication or supplements to affect lipid, insulin, or glucose metabolism were excluded. Fasting glucose levels, insulin, and lipoproteins (total, HDL-high density and LDL-low density lipoprotein cholesterol) were compared between the groups with different HOMA IR. After analysis of data distribution, F-test and t-test were provided to compare variances and mean values. Results: The evaluation shows that the kind of cholesterol is crucial for a possible relationship with glucose metabolism and consequently confirms the changes of lipoproteins (HDL and LDL) by HOMA IR cut-off 3.63. Conclusions: The results of patients divided by HOMA IR cut-off 3.63 also suggest possible changes in the regulation of glucose metabolism and lipoprotein concentrations (HDL and LDL).
- MeSH
- cholesterol MeSH
- HDL-cholesterol MeSH
- inzulin MeSH
- inzulinová rezistence * MeSH
- krevní glukóza MeSH
- lidé MeSH
- triglyceridy MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Česká republika MeSH
