Food Recognition System: A New Approach Based on Wavelet-LSTM
| Autor: | Ghulam Hussain |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Sukkur IBA Journal of Emerging Technologies, Vol 6, Iss 1 (2023) |
| Druh dokumentu: | article |
| ISSN: | 2616-7069 2617-3115 |
| DOI: | 10.30537/sjet.v6i1.1258 |
| Popis: | An automated system for analyzing daily dietary intake is essential for human well-being and healthcare. This work presents a novel wearable necklace embedded with a piezoelectric sensor and a microcontroller to monitor food ingestion of users. To effectively represent the food ingestion patterns, the sensor signal is dynamically segmented using a bidirectional search technique. Each segmented food intake pattern consists of a chewing sequence and a swallow peak. We exploit wavelet transform to decompose the complex food ingestion patterns, collected by the sensor, into frequency sub-bands at discrete scales. The frequency sub-bands are used as sequences to train long short-term memory (LSTM) for the recognition of 5 food categories. Our proposed recognition model based on wavelet-LSTM recognizes 5 food classes with an accuracy of 98.1% |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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