Feasibility analysis of gesture recognition based human wearable electronic accessories
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2022.
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Brac University
2023
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| 在線閱讀: | http://hdl.handle.net/10361/21017 |
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10361-21017 |
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10361-210172023-09-20T05:48:18Z Feasibility analysis of gesture recognition based human wearable electronic accessories Taki, Khan Sakib Nur Tonny, Jannatul Ferdous Nahin, S.H.M Bhuian, Mohammed Belal Hossain Department of Electrical and Electronic Engineering, Brac University HRM ESP8266 wifi module MAX30100 sensor Bpm MCU MAXHR LED IoT Electronic circuit design--Computer programs Internet of things This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 46-49). The Oximeter is commonly used on the finger tips for better analysis of the oxygen saturation on the blood. Still there are some errors to be aware of during the scans. It has a tendency to be accuracy 90% of the time. Furthermore, if there are possibilities to get some errors from scanning the part of the body with less skin density such as fingers, scanning on the wrist will have far more errors than this. Yet, from comparing the two measurements we can find the difference between the error and add them on the taken analysis to get the actual result. Now it is as simple as adding the error of the analysis gap we get both the wrist and the fingertip. After comparing with the market best oximeter with the reading of different individuals the accuracy has been checked and corrected. This system can be efficient for monitoring the COVID-19 patients as they mostly face the falling oxygen saturation sta Khan Sakib Nur Taki Jannatul Ferdous Tonny S.H.M Nahin B. Electrical and Electronic Engineering 2023-09-19T06:42:48Z 2023-09-19T06:42:48Z 2022 2022-11 Thesis ID 15321005 ID 15321011 ID 15321018 http://hdl.handle.net/10361/21017 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 55 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
HRM ESP8266 wifi module MAX30100 sensor Bpm MCU MAXHR LED IoT Electronic circuit design--Computer programs Internet of things |
| spellingShingle |
HRM ESP8266 wifi module MAX30100 sensor Bpm MCU MAXHR LED IoT Electronic circuit design--Computer programs Internet of things Taki, Khan Sakib Nur Tonny, Jannatul Ferdous Nahin, S.H.M Feasibility analysis of gesture recognition based human wearable electronic accessories |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2022. |
| author2 |
Bhuian, Mohammed Belal Hossain |
| author_facet |
Bhuian, Mohammed Belal Hossain Taki, Khan Sakib Nur Tonny, Jannatul Ferdous Nahin, S.H.M |
| format |
Thesis |
| author |
Taki, Khan Sakib Nur Tonny, Jannatul Ferdous Nahin, S.H.M |
| author_sort |
Taki, Khan Sakib Nur |
| title |
Feasibility analysis of gesture recognition based human wearable electronic accessories |
| title_short |
Feasibility analysis of gesture recognition based human wearable electronic accessories |
| title_full |
Feasibility analysis of gesture recognition based human wearable electronic accessories |
| title_fullStr |
Feasibility analysis of gesture recognition based human wearable electronic accessories |
| title_full_unstemmed |
Feasibility analysis of gesture recognition based human wearable electronic accessories |
| title_sort |
feasibility analysis of gesture recognition based human wearable electronic accessories |
| publisher |
Brac University |
| publishDate |
2023 |
| url |
http://hdl.handle.net/10361/21017 |
| work_keys_str_mv |
AT takikhansakibnur feasibilityanalysisofgesturerecognitionbasedhumanwearableelectronicaccessories AT tonnyjannatulferdous feasibilityanalysisofgesturerecognitionbasedhumanwearableelectronicaccessories AT nahinshm feasibilityanalysisofgesturerecognitionbasedhumanwearableelectronicaccessories |
| _version_ |
1814307580326969344 |