Fall-Detection Algorithm Using 3-Axis Acceleration: Combination with Simple Threshold and Hidden Markov Model
Falls are a serious medical and social problem among the elderly. This has led to the development of automatic fall-detection systems. To detect falls, a fall-detection algorithm that combines a simple threshold method and hidden Markov model (HMM) using 3-axis acceleration is proposed. To apply the...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2014/896030 |
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| _version_ | 1832558300689858560 |
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| author | Dongha Lim Chulho Park Nam Ho Kim Sang-Hoon Kim Yun Seop Yu |
| author_facet | Dongha Lim Chulho Park Nam Ho Kim Sang-Hoon Kim Yun Seop Yu |
| author_sort | Dongha Lim |
| collection | DOAJ |
| description | Falls are a serious medical and social problem among the elderly. This has led to the development of automatic fall-detection systems. To detect falls, a fall-detection algorithm that combines a simple threshold method and hidden Markov model (HMM) using 3-axis acceleration is proposed. To apply the proposed fall-detection algorithm and detect falls, a wearable fall-detection device has been designed and produced. Several fall-feature parameters of 3-axis acceleration are introduced and applied to a simple threshold method. Possible falls are chosen through the simple threshold and are applied to two types of HMM to distinguish between a fall and an activity of daily living (ADL). The results using the simple threshold, HMM, and combination of the simple method and HMM were compared and analyzed. The combination of the simple threshold method and HMM reduced the complexity of the hardware and the proposed algorithm exhibited higher accuracy than that of the simple threshold method. |
| format | Article |
| id | doaj-art-27be909c38dc48498f9691888ba9f48f |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-27be909c38dc48498f9691888ba9f48f2025-02-03T01:32:41ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/896030896030Fall-Detection Algorithm Using 3-Axis Acceleration: Combination with Simple Threshold and Hidden Markov ModelDongha Lim0Chulho Park1Nam Ho Kim2Sang-Hoon Kim3Yun Seop Yu4Department of Electrical, Electronic and Control Engineering and IITC, Hankyong National University, 327 Chungang-no, Anseong, Gyeonggi-do 456-749, Republic of KoreaDepartment of Electrical, Electronic and Control Engineering and IITC, Hankyong National University, 327 Chungang-no, Anseong, Gyeonggi-do 456-749, Republic of KoreaDepartment of Electrical, Electronic and Control Engineering and IITC, Hankyong National University, 327 Chungang-no, Anseong, Gyeonggi-do 456-749, Republic of KoreaDepartment of Electrical, Electronic and Control Engineering and IITC, Hankyong National University, 327 Chungang-no, Anseong, Gyeonggi-do 456-749, Republic of KoreaDepartment of Electrical, Electronic and Control Engineering and IITC, Hankyong National University, 327 Chungang-no, Anseong, Gyeonggi-do 456-749, Republic of KoreaFalls are a serious medical and social problem among the elderly. This has led to the development of automatic fall-detection systems. To detect falls, a fall-detection algorithm that combines a simple threshold method and hidden Markov model (HMM) using 3-axis acceleration is proposed. To apply the proposed fall-detection algorithm and detect falls, a wearable fall-detection device has been designed and produced. Several fall-feature parameters of 3-axis acceleration are introduced and applied to a simple threshold method. Possible falls are chosen through the simple threshold and are applied to two types of HMM to distinguish between a fall and an activity of daily living (ADL). The results using the simple threshold, HMM, and combination of the simple method and HMM were compared and analyzed. The combination of the simple threshold method and HMM reduced the complexity of the hardware and the proposed algorithm exhibited higher accuracy than that of the simple threshold method.http://dx.doi.org/10.1155/2014/896030 |
| spellingShingle | Dongha Lim Chulho Park Nam Ho Kim Sang-Hoon Kim Yun Seop Yu Fall-Detection Algorithm Using 3-Axis Acceleration: Combination with Simple Threshold and Hidden Markov Model Journal of Applied Mathematics |
| title | Fall-Detection Algorithm Using 3-Axis Acceleration: Combination with Simple Threshold and Hidden Markov Model |
| title_full | Fall-Detection Algorithm Using 3-Axis Acceleration: Combination with Simple Threshold and Hidden Markov Model |
| title_fullStr | Fall-Detection Algorithm Using 3-Axis Acceleration: Combination with Simple Threshold and Hidden Markov Model |
| title_full_unstemmed | Fall-Detection Algorithm Using 3-Axis Acceleration: Combination with Simple Threshold and Hidden Markov Model |
| title_short | Fall-Detection Algorithm Using 3-Axis Acceleration: Combination with Simple Threshold and Hidden Markov Model |
| title_sort | fall detection algorithm using 3 axis acceleration combination with simple threshold and hidden markov model |
| url | http://dx.doi.org/10.1155/2014/896030 |
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