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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | FALL DETECTION & DAILY LIVING ACTIVITY RECOGNITION |
| Authors Name: | VYSHALI. S , Dr. S. Raja Mohamed |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_190936
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| Published Paper Id: | IJNRD2304210 |
| Published In: | Volume 8 Issue 4, April-2023 |
| DOI: | |
| Abstract: | The number of elder people in countries were increasing in number due to cultural life. Most of them prefer in be independent and leads in fall. Fall was often leads in serious and even severe injuries which leads in cause death of elder people. In address that problem, since must be necessary to implement fall discovering systems. In that project, implementing a machine learning algorithm for fall discovery and living activity monitoring and recognition. Using acceleration with angular velocity datas from non private datasets are used in recognizing the 9 different activity which includes the fall and activity of frequently living. From the angular velocity with acceleration frequency domain features, datas, extracting time and providing a classification algorithms. The project proposes a machine learning algorithm for fall detecting and living activities recognizing, Convolution Neural Network was used in Classification. the first better contribution has been shown with the feature for fall discovery. More importantly, using the value of mean for acceleration and achieving the fall discovery accurate and precisions as best one. Even though, value of mean for acceleration was not shown a new appearance since was pointed in previously proposals in classify ADLs, the value of mean of the triaxial acceleration is not utilizing as the features of classification the entire falls. |
| Keywords: | elder fall detect, living activity recognition, convolutional neural network, dataset values. |
| Cite Article: | "FALL DETECTION & DAILY LIVING ACTIVITY RECOGNITION", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 4, page no.c67-c72, April-2023, Available :http://www.ijnrd.org/papers/IJNRD2304210.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2304210 Registration ID: 190936 Published In: Volume 8 Issue 4, April-2023 DOI (Digital Object Identifier): Page No: c67-c72 Country: coimbatore, Tamil Nadu, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2304210 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2304210 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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