Classifying Pre-Radiographic Osteoarthritis of the Knee Using Wearable Acoustics Sensing at the Point of Care.

This study was undertaken to determine if knee acoustic emissions (KAE) measured at the point of care with a wearable device can classify knees with pre-radiographic osteoarthritis (pre-OA) from healthy knees. We performed a single-center cross-sectional observational study comparing KAE in healthy knees to knees with clinical symptoms compatible with knee OA that did not meet classification criteria for radiographic knee OA. KAE were measured during scripted maneuvers performed in clinic exam rooms or similarly noisy medical center locations in healthy (n=20), pre-OA (n=11), and, for comparison, OA (n=12) knees.

Active Vibrational Achilles Tendon Sensing for Identifying and Characterizing Inflammatory Symptomatology in Enthesitis Related Arthritis.

Objective: This study explores the potential of active vibrational sensing as a digital biomarker to identify and characterize inflammatory symptomatology in the Achilles tendon and its entheses in juvenile idiopathic arthritis (JIA), particularly enthesitis related arthritis (ERA), a subcategory of JIA.

Methods: Active vibrational data were non-invasively recorded using a miniature coin vibration motor and accelerometer. Twenty active vibration recordings from children diagnosed with JIA were used in the analysis.

Enabling Continuous Breathing-Phase Contextualization via Wearable-Based Impedance Pneumography and Lung Sounds: A Feasibility Study.

Chronic respiratory diseases affect millions and are leading causes of death in the US and worldwide. Pulmonary auscultation provides clinicians with critical respiratory health information through the study of Lung Sounds (LS) and the context of the breathing-phase and chest location in which they are measured. Existing auscultation technologies, however, do not enable the simultaneous measurement of this context, thereby potentially limiting computerized LS analysis.

Mid-Activity and At-Home Wearable Bioimpedance Elucidates an Interpretable Digital Biomarker of Muscle Fatigue.

Objective: Muscle health and decreased muscle performance (fatigue) quantification has proven to be an invaluable tool for both athletic performance assessment and injury prevention. However, existing methods estimating muscle fatigue are infeasible for everyday use. Wearable technologies are feasible for everyday use and can enable discovery of digital biomarkers of muscle fatigue.

Validating Adhesive-Free Bioimpedance of the Leg in Mid-Activity and Uncontrolled Settings.

Objective: Musculoskeletal health monitoring is limited in everyday settings where patient symptoms can substantially change - delaying treatment and worsening patient outcomes. Wearable technologies aim to quantify musculoskeletal health outside clinical settings but sensor constraints limit usability. Wearable localized multi-frequency bioimpedance assessment (MFBIA) shows promise for tracking musculoskeletal health but relies on gel electrodes, hindering extended at-home use.

Wearable Mid-Activity Measurement of Lower Limb Electrical Bioimpedance Estimates Vertical Ground Reaction Force Features.

In recent years, wearable mid-activity electrical bioimpedance (EBI) sensing has been used to non-invasively track changes in edema and swelling levels within human joints. While the physiological origin of the changes in mid-activity EBI measurements have been demonstrated, EBI waveform patterns during activity have not been explored. In this work, we present a novel approach to extract waveform features from EBI measurements during gait to estimate the changes in vertical ground reaction forces (vGRF) corresponding to fatigue.

Quantifying Rheumatoid Arthritis Disease Activity Using a Multimodal Sensing Knee Brace.

Objective: Rheumatoid arthritis (RA) is a chronic inflammatory syndrome that features painful and destructive joint disease. Aggressive disease-modifying treatment can result in reduced symptoms and protection from irreversible joint damage; however, assessment of treatment efficacy is currently based largely on subjective measures of patient and physician impressions. In this work, we address this compelling need to provide an accurate and quantitative capability for monitoring joint health in patients with RA.

A Wearable Multimodal Sensing System for Tracking Changes in Pulmonary Fluid Status, Lung Sounds, and Respiratory Markers.

Heart failure (HF) exacerbations, characterized by pulmonary congestion and breathlessness, require frequent hospitalizations, often resulting in poor outcomes. Current methods for tracking lung fluid and respiratory distress are unable to produce continuous, holistic measures of cardiopulmonary health. We present a multimodal sensing system that captures bioimpedance spectroscopy (BIS), multi-channel lung sounds from four contact microphones, multi-frequency impedance pneumography (IP), temperature, and kinematics to track changes in cardiopulmonary status.

An Integrated Multimodal Knee Brace Enabling Mid-Activity Tracking for Joint Health Assessment.

Developments in wearable technologies created opportunities for non-invasive joint health assessment while subjects perform daily activities during rehabilitation and recovery. However, existing state-of-art solutions still require a health professional or a researcher to set up the device, and most of them are not convenient for at-home use. In this paper, we demonstrate the latest version of the multimodal knee brace that our lab previously developed.

Quantifying Signal Quality for Joint Acoustic Emissions Using Graph-Based Spectral Embedding.

We present a new method for quantifying signal quality of joint acoustic emissions (JAEs) from the knee during unloaded flexion/extension (F/E) exercises. For ten F/E cycles, JAEs were recorded, in a clinical setting, from 34 healthy knees and 13 with a meniscus tear (n=24 subjects). The recordings were first segmented by F/E cycle and described using time and frequency domain features.

A Novel Accelerometer Mounting Method for Sensing Performance Improvement in Acoustic Measurements From the Knee.

In this study, we propose a new mounting method to improve accelerometer sensing performance in the 50 Hz-10 kHz frequency band for knee sound measurement. The proposed method includes a thin double-sided adhesive tape for mounting and a 3D-printed custom-designed backing prototype. In our mechanical setup with an electrodynamic shaker, the measurements showed a 13 dB increase in the accelerometer's sensing performance in the 1-10 kHz frequency band when it is mounted with the craft tape under 2 N backing force applied through low-friction tape.

An Interpretable Experimental Data Augmentation Method to Improve Knee Health Classification Using Joint Acoustic Emissions.

The characteristics of joint acoustic emissions (JAEs) measured from the knee have been shown to contain information regarding underlying joint health. Researchers have developed methods to process JAE measurements and combined them with machine learning algorithms for knee injury diagnosis. While these methods are based on JAEs measured in controlled settings, we anticipate that JAE measurements could enable accessible and affordable diagnosis of acute knee injuries also in field-deployable settings.

Detection of Meniscal Tear Effects on Tibial Vibration Using Passive Knee Sound Measurements.

Objective: To evaluate whether non-invasive knee sound measurements can provide information related to the underlying structural changes in the knee following meniscal tear. These changes are explained using an equivalent vibrational model of the knee-tibia structure.

Methods: First, we formed an analytical model by modeling the tibia as a cantilever beam with the fixed end being the knee.