OBJECTIVE: We designed and validated a portable electrical bioimpedance (EBI) system to quantify knee joint health. METHODS: Five separate experiments were performed to demonstrate the: 1) ability of the EBI system to assess knee injury and recovery; 2) interday variability of knee EBI measurements; 3) sensitivity of the system to small changes in interstitial fluid volume; 4) reducing the error of EBI measurements using acceleration signals; and 5) use of the system with dry electrodes integrated to a wearable knee wrap. RESULTS: 1) The absolute difference in resistance ( R) and reactance (X) from the left to the right knee was able to distinguish injured and healthy knees (p < 0.05); the absolute difference in R decreased significantly (p < 0.05) in injured subjects following rehabilitation. 2) The average interday variability (standard deviation) of the absolute difference in knee R was 2.5 Ω and for X was 1.2 Ω. 3) Local heating/cooling resulted in a significant decrease/increase in knee R (p < 0.01). 4) The proposed subject position detection algorithm achieved 97.4% leave-one subject out cross-validated accuracy and 98.2% precision in detecting when the subject is in the correct position to take measurements. 5) Linear regression between the knee R and X measured using the wet electrodes and the designed wearable knee wrap were highly correlated ( R2 = 0.8 and 0.9, respectively). CONCLUSION: This study demonstrates the use of wearable EBI measurements in monitoring knee joint health. SIGNIFICANCE: The proposed wearable system has the potential for assessing knee joint health outside the clinic/lab and help guide rehabilitation.
OBJECTIVE: We designed and validated a portable electrical bioimpedance (EBI) system to quantify knee joint health. METHODS: Five separate experiments were performed to demonstrate the: 1) ability of the EBI system to assess knee injury and recovery; 2) interday variability of knee EBI measurements; 3) sensitivity of the system to small changes in interstitial fluid volume; 4) reducing the error of EBI measurements using acceleration signals; and 5) use of the system with dry electrodes integrated to a wearable knee wrap. RESULTS: 1) The absolute difference in resistance ( R) and reactance (X) from the left to the right knee was able to distinguish injured and healthy knees (p < 0.05); the absolute difference in R decreased significantly (p < 0.05) in injured subjects following rehabilitation. 2) The average interday variability (standard deviation) of the absolute difference in knee R was 2.5 Ω and for X was 1.2 Ω. 3) Local heating/cooling resulted in a significant decrease/increase in knee R (p < 0.01). 4) The proposed subject position detection algorithm achieved 97.4% leave-one subject out cross-validated accuracy and 98.2% precision in detecting when the subject is in the correct position to take measurements. 5) Linear regression between the knee R and X measured using the wet electrodes and the designed wearable knee wrap were highly correlated ( R2 = 0.8 and 0.9, respectively). CONCLUSION: This study demonstrates the use of wearable EBI measurements in monitoring knee joint health. SIGNIFICANCE: The proposed wearable system has the potential for assessing knee joint health outside the clinic/lab and help guide rehabilitation.
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