Automatic limb identification and sleeping parameters assessment for pressure ulcer prevention.
Pressure ulcers (PUs) are common among vulnerable patients such as elderly, bedridden and diabetic. PUs are very painful for patients and costly for hospitals and nursing homes. Assessment of sleeping parameters on at-risk limbs is critical for ulcer prevention. An effective assessment depends on automatic identification and tracking of at-risk limbs. An accurate limb identification can be used to analyze the pressure distribution and assess risk for each limb. In this paper, we propose a graph-based clustering approach to extract the body limbs from the pressure data collected by a commercial pressure map system. A robust signature-based technique is employed to automatically label each limb. Finally, an assessment technique is applied to evaluate the experienced stress by each limb over time. The experimental results indicate high performance and more than 94% average accuracy of the proposed approach.
Quality of Life Technology Laboratory, The University of Texas at Dallas, Richardson, TX 75080, United States. Electronic address: mxb112230@utdallas.edu.
Maziyar
M
Baran Pouyan
Quality of Life Technology Laboratory, The University of Texas at Dallas, Richardson, TX 75080, United States. Electronic address: birjandtalab@utdallas.edu.
Javad
J
Birjandtalab
Quality of Life Technology Laboratory, The University of Texas at Dallas, Richardson, TX 75080, United States. Electronic address: nourani@utdallas.edu.
Mehrdad
M
Nourani
Presbyterian Wound Care Clinic, Dallas, TX 75231, United States. Electronic address: healerone@aol.com.
M D
MD
Matthew Pompeo
D001330:Electronic Data Processing / Q000379:methods*; D005121:Extremities / Q000098:blood supply / Q000503:physiopathology*; D005260:Female; D006801:Humans; D008297:Male; D003668:Pressure Ulcer / Q000517:prevention & control*; D012890:Sleep
Assessment; Bed-inclination; Graph clustering; Limb identification; Pressure image; Pressure ulcer