000			01608nam a22001577a 4500
082			_a610
100			_aKazim, Assad Ali _9132917
245			_aDevelopment of Machine Learning Model for Classification of No Specific Chronic Lower Back Patients from Healthy Patients Usin Spinal Kinematic Data Through Motion Capture (MOCAP) / _cAssad Ali Kazim
264			_aIslamabad : _bSMME- NUST; _c2025.
300			_a70p. _bSoft Copy _c30cm
500			_aNon-specific lower back pain remains a global physiological disability surpassing pathological diseases. Its diagnosis through modern machines are expensive and frequent doses of radiation lead to deterioration of body cells. Recently with development of allied technologies such as Motion Capture (MoCap) can evaluate skeletal motion of the patient. This technology vastly used in cinematography has a hidden usage for diagnosis of patients with NSLBP. Through various sampling of motion and effective utilisation of Machine Learning, we can classify a healthy patient from NSLBP patient. Various supervised learning models such as Scalar Vector Machine (SVM), Random Forest (RF), XGBoost and ANN have shown promising results which reflects that such AI tools can predict patients having NSLBP. Effective utilization can lead to exact determination of location where said problem is being developed in the patient through various motion examinations.
650			_aMS Biomedical Engineering (BME) _9119509
700			_aSupervisor : Dr. Asim Waris _9119477
856			_uhttp://10.250.8.41:8080/xmlui/handle/123456789/57255
942			_2ddc _cTHE
999			_c615942 _d615942