| 000 | 00912nam a22001937a 4500 | ||
|---|---|---|---|
| 999 |
_c57128 _d57128 |
||
| 040 | _cRiphah International University | ||
| 082 |
_a621.31 _bAZA |
||
| 100 | _aAzam Khan (27711) | ||
| 245 | _aArtificial intelligence based non-invasive blood glucose level estimation using PPG sensor | ||
| 260 |
_aIslamabad _b(Unpublished) _c2024 |
||
| 300 |
_axiii , 43 p. _b: ill. _c; 30 cm. _e+CD |
||
| 500 | _aSubmitted in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering to the Faculty of Engineering and Applied Sciences. | ||
| 500 | _aIncludes bibliographical references. | ||
| 500 | _aThesis supervisor: Dr. Shahreyar Najam | ||
| 502 | _aThesis (M.S.)--Riphah International University, 2024 | ||
| 546 | _aEnglish | ||
| 650 |
_aElectrical engineering _vpower line interference _vPrimatene ventricular _vMotion artifact _vSingle wave _vEnergy _vFEAS |
||
| 942 | _cTH | ||