| 姜鸣,王哲龙,刘晓博,赵红宇,胡耀华.基于BSN和CHMMs的人体日常动作识别方法研究[J].,2013,53(1): |
| 基于BSN和CHMMs的人体日常动作识别方法研究 |
| Research on human daily activity recognition method based on BSN and CHMMs |
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| DOI：10.7511/dllgxb201301021 |
| 中文关键词: 人体传感器网络 动作识别 耦合隐马尔可夫模型 数据融合 |
| 英文关键词: body sensor networks activity recognition coupled HMM data fusion |
| 基金项目:国家地震行业科研专项资助项目(200808075);国家科技重大专项子课题资助项目(2010ZX04007-011-5). |
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| 中文摘要: |
| 应用人体传感器网络(body sensor networks,BSN)识别人体日常动作可以有效地提高对老年人、慢性病人,以及术后病人等特殊人群的医疗监护质量．为此建立了一个基于BSN的人体日常动作监督平台,应用采集到的加速度信号识别9个常见的人体日常动作．针对动作识别过程中存在的多传感器数据融合问题,提出一种基于耦合隐马尔可夫模型(coupled hidden Markov models,CHMMs)的动作识别方法．实验结果显示,与已有动作识别方法相比,提出的基于CHMMs的动作识别方法的识别正确率有明显的提高． |
| 英文摘要: |
| Body sensor networks (BSN) may offer continuous monitoring of human activities in a range of healthcare areas, including caring the elderly, helping chronic patients, and monitoring the recovery of post-operative patients. A monitoring platform based on BSN is established for recognizing 9 human daily activities using acceleration signal. A activity recognition method based on coupled hidden Markov models (CHMMs) is proposed for multi-sensor data fusion. The experimental results show that compared with previous methods, the proposed method can achieve satisfactory performance for human daily activity recognition. |
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