Literature DB >> 26444814

Body posture recognition and turning recording system for the care of bed bound patients.

Rong-Shue Hsiao1, Zhenqiang Mi2, Bo-Ru Yang3, Lih-Jen Kau1, Mekuanint Agegnehu Bitew1, Tzu-Yu Li1.   

Abstract

This paper proposes body posture recognition and turning recording system for assisting the care of bed bound patients in nursing homes. The system continuously detects the patient's body posture and records the length of time for each body posture. If the patient remains in the same body posture long enough to develop pressure ulcers, the system notifies caregivers to change the patient's body posture. The objective of recording is to provide the log of body turning for querying of patients' family members. In order to accurately detect patient's body posture, we developed a novel pressure sensing pad which contains force sensing resistor sensors. Based on the proposed pressure sensing pad, we developed a bed posture recognition module which includes a bed posture recognition algorithm. The algorithm is based on fuzzy theory. The body posture recognition algorithm can detect the patient's bed posture whether it is right lateral decubitus, left lateral decubitus, or supine. The detected information of patient's body posture can be then transmitted to the server of healthcare center by the communication module to perform the functions of recording and notification. Experimental results showed that the average posture recognition accuracy for our proposed module is 92%.

Entities:  

Keywords:  Bed sensing; body posture; force sensing resistor; healthcare; posture recognition

Mesh:

Year:  2015        PMID: 26444814     DOI: 10.3233/THC-151088

Source DB:  PubMed          Journal:  Technol Health Care        ISSN: 0928-7329            Impact factor:   1.285


  3 in total

Review 1.  The potential of artificial intelligence to improve patient safety: a scoping review.

Authors:  David W Bates; David Levine; Ania Syrowatka; Masha Kuznetsova; Kelly Jean Thomas Craig; Angela Rui; Gretchen Purcell Jackson; Kyu Rhee
Journal:  NPJ Digit Med       Date:  2021-03-19

Review 2.  Using Machine Learning Technologies in Pressure Injury Management: Systematic Review.

Authors:  Mengyao Jiang; Yuxia Ma; Siyi Guo; Liuqi Jin; Lin Lv; Lin Han; Ning An
Journal:  JMIR Med Inform       Date:  2021-03-10

Review 3.  Artificial Intelligence in Brain Tumour Surgery-An Emerging Paradigm.

Authors:  Simon Williams; Hugo Layard Horsfall; Jonathan P Funnell; John G Hanrahan; Danyal Z Khan; William Muirhead; Danail Stoyanov; Hani J Marcus
Journal:  Cancers (Basel)       Date:  2021-10-07       Impact factor: 6.639

  3 in total

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