類似資料: PREDICTING THE DEPTH OF ANESTHESIA FOR OPERATING PATIENT USING MUSIC-BASED SPECTRAL FEATURES OF EEG SIGNALS /
- PREDICTING THE DEPTH OF ANESTHESIA FOR OPERATING PATIENT USING MUSIC-BASED SPECTRAL FEATURES OF EEG SIGNALS
- CLASSIFICATION PERFORMANCE EVALUATION OF DIFFERENT RHYTHMIC BANDS OF EEG BASED ANESTHESIA MONITORING /
- DEVELOPING A STANDARD MATHEMATICAL METHOD TO MEASURE THE LEVEL OF INTER-TRIAL & INTER-SUBJECT INCONSISTENCY FOR EEG SIGNAL /
- DEVELOPMENT OF THE SMARTPHONE ACCESSING FACILITIES AND SELF OPERATED WHEELCHAIR FOR THE UPPER LIMB PARALYZED PATIENT THROUGH TDS (TONGUE DRIVE SYSTEM) /
- DEVELOPMENT OF A SMART PATIENT-DATA MANAGEMENT SYSTEM FOR HOSPITALS /
- DESIGN AND DEVELOPMENT OF A HYBRID PNEUMATIC PUMP FOR VARICOSE VEIN PATIENT /
トピック: Biomedical Engineering.
- Introduction to Biomedical Equipment Technology /
- Medical instrumentation : application and design /
- Biomedical engineering fundamentals /
- Biomedical engineering handbook /
- Biomedical instrumentation and measurements /
- A STUDY AND REVIEWER OPINION ON DIFFERENT IMAGING MODALITIES USED IN HDRBRACHYTHERAPY FOR PROSTATE /
トピック: This Thesis Paper of BME in M.Sc. Program.
- DEVELOPMENT OF CHICKEN EGG WHITE AND MUPIROCIN LOADED HYDROGEL DRESSING MATERIAL FOR INHIBITION OF BACTERIAL GROWTH /
- DEVELOPMENT OF A CLINICAL DIAGNOSIS AND DECISION SUPPORT SYSTEM FOR CHEST RADIOGRAPHY USING CNN /
- ATTEMPTED MOVEMENT CLASSIFICATION OF SPINAL CORD INJURED PATIENTS COMBINING CNN AND LSTM NETWORK /
- DEVELOPMENT OF CERAMIDE AND HONEY BASED BIODEGRADABLE DRESSING MATERIALS FOR THE APPLICATION TO BURN SKIN /
- PREDICTING THE DEPTH OF ANESTHESIA FOR OPERATING PATIENT USING MUSIC-BASED SPECTRAL FEATURES OF EEG SIGNALS /
著者: Rahman, M. N. Nashid
著者: Supervised by Asst. Prof. Dr. Md. Asadur Rahman
- DEVELOPMENT OF A CLINICAL DIAGNOSIS AND DECISION SUPPORT SYSTEM FOR CHEST RADIOGRAPHY USING CNN /
- ATTEMPTED MOVEMENT CLASSIFICATION OF SPINAL CORD INJURED PATIENTS COMBINING CNN AND LSTM NETWORK /
- PREDICTING THE DEPTH OF ANESTHESIA FOR OPERATING PATIENT USING MUSIC-BASED SPECTRAL FEATURES OF EEG SIGNALS /