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    Sternal precautions are a universal part of the discharge education for post-sternotomy patients to reduce the risk of sternal complications. However, they are always designed based on physical therapists' or surgeons' subjective judgment without any objective evidence. Thus, they could be overly restrictive to hinder the patients' recovery, physically and psychologically. To fill this gap, this paper proposes a digital biomarker to estimate chest expansion during sit-to-stand transitions based on wearable inertial sensing and data fusion technologies. First, we carried out bench tests to evaluate the reliability of the digital biomarker to represent relative sensor rotation. We also verified effectiveness of this digital biomarker to detect subtle skin extension in proactive chest expansion trials by 11 healthy volunteers. Then, we measured the digital biomarker during sit-to-stand transitions with different strategies and some daily routine activities (walking, sitting, and standing) performed by the healthy volunteers and 22 post-sternotomy patients. The comparison between these measurements evaluated the effectiveness of several known guidelines of sternal precautions for sit-to-stand transitions. The results showed that first, pushing up from a chair by taking support from armrests induced larger chest expansion ( p = 0.009 ) compared with sit-to-stand transition while keeping the arms relaxed; second, crossing the arms or hugging a pillow can help reduce chest expansion ( ) compared with keeping the arms relaxed during sit-to-stand transitions; third, pushing up while taking support from a frontal support (e.g., table or walker) induced the same level of chest expansion ( ) as that during sit-to-stand transition while keeping the arms relaxed.


    Changhong Wang, Rahul Goel, Maria Noun, Ravi K Ghanta, Bijan Najafi. Wearable Sensor-Based Digital Biomarker to Estimate Chest Expansion During Sit-to-Stand Transitions-A Practical Tool to Improve Sternal Precautions in Patients Undergoing Median Sternotomy. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society. 2020 Jan;28(1):165-173

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    PMID: 31714229

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