Ubiquitous blood pressure (BP) monitoring is needed to improve hypertension detection and control and is becoming feasible due to recent technological advances such as in wearable sensing. Pulse transit time (PTT) represents a well-known, potential approach for ubiquitous BP monitoring. The goal of this review is to facilitate the achievement of reliable, ubiquitous BP monitoring via PTT. We explain the conventional BP measurement methods and their limitations; present models to summarize the theory of the PTT-BP relationship; outline the approach while pinpointing the key challenges; overview the previous work towards putting the theory to practice; make suggestions for best practice and future research; and discuss realistic expectations for the approach.

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) inter-day 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; (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 inter-day variability (standard deviation) of the absolute difference in knee R was 2.5Ω, 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 work 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.

These proposed methods have the potential for enabling knee joint acoustics measurement outside the clinic/lab and permitting long-term monitoring of knee health for patients rehabilitating an acute knee joint injury.

We present a robust vector bioimpedance measurement system for longitudinal knee joint health assessment, capable of acquiring high resolution static (slowly varying over the course of hours to days) and dynamic (rapidly varying on the order of milli-seconds) bioresistance and bioreactance signals. Occupying an area of 78×90 mm(2) and consuming 0.25 W when supplied with ±5 V, the front-end achieves a dynamic range of 345 Ω and noise floor of 0.018 mΩrms (resistive) and 0.055 mΩrms (reactive) within a bandwidth of 0.1-20 Hz. A microcontroller allows real-time calibration to minimize errors due to environmental variability (e.g., temperature) that can be experienced outside of lab environments, and enables data storage on a micro secure digital card. The acquired signals are then processed using customized physiology-driven algorithms to extract musculoskeletal (edema) and cardiovascular (local blood volume pulse) features from the knee joint. In a feasibility study, we found statistically significant differences between the injured and contralateral static knee impedance measures for two subjects with recent unilateral knee injury compared to seven controls. Specifically, the impedance was lower for the injured knees, supporting the physiological expectations for increased edema and damaged cell membranes. In a second feasibility study, we demonstrate the sensitivity of the dynamic impedance measures with a cold-pressor test, with a 20 mΩ decrease in the pulsatile resistance associated with increased downstream peripheral vascular resistance. The proposed system will serve as a foundation for future efforts aimed at quantifying joint health status continuously during normal daily life.

Knee-joint sounds could potentially be used to noninvasively probe the physical and/or physiological changes in the knee associated with rehabilitation following acute injury. In this paper, a system and methods for investigating the consistency of knee-joint sounds during complex motions in silent and loud background settings are presented. The wearable hardware component of the system consists of a microelectromechanical systems microphone and inertial rate sensors interfaced with a field programmable gate array-based real-time processor to capture knee-joint sound and angle information during three types of motion: flexion-extension (FE), sit-to-stand (SS), and walking (W) tasks. The data were post-processed to extract high-frequency and short-duration joint sounds (clicks) with particular waveform signatures. Such clicks were extracted in the presence of three different sources of interference: background, stepping, and rubbing noise. A histogram-vector Vn(→) was generated from the clicks in a motion-cycle n, where the bin range was 10°. The Euclidean distance between a vector and the arithmetic mean Vav(→) of all vectors in a recording normalized by the Vav(→) is used as a consistency metric dn. Measurements from eight healthy subjects performing FE, SS, and W show that the mean (of mean) consistency metric for all subjects during SS (μ [ μ (dn)] = 0.72 in silent, 0.85 in loud) is smaller compared with the FE (μ [ μ (dn)] = 1.02 in silent, 0.95 in loud) and W ( μ [ μ (dn)] = 0.94 in silent, 0.97 in loud) exercises, thereby implying more consistent click-generation during SS compared with the FE and W. Knee-joint sounds from one subject performing FE during five consecutive work-days (μ [ μ (dn) = 0.72) and five different times of a day (μ [ μ (dn) = 0.73) suggests high consistency of the clicks on different days and throughout a day. This work represents the first time, to the best of our knowledge, that joint sound consistency has been quantified in ambulatory subjects performing every-day activities (e.g., SS, walking). Moreover, it is demonstrated that noise inherent with joint-sound recordings during complex motions in uncontrolled settings does not prevent joint-sound-features from being detected successfully.