Detection of pathological mechano-acoustic signatures using precision accelerometer contact microphones in patients with pulmonary disorders

Abstract

Monitoring pathological mechano-acoustic signals emanating from the lungs is critical for timely and cost-effective healthcare delivery. Adventitious lung sounds including crackles, wheezes, rhonchi, bronchial breath sounds, stridor or pleural rub and abnormal breathing patterns function as essential clinical biomarkers for the early identification, accurate diagnosis and monitoring of pulmonary disorders. Here, we present a wearable sensor module comprising of a hermetically encapsulated, high precision accelerometer contact microphone (ACM) which enables both episodic and longitudinal assessment of lung sounds, breathing patterns and respiratory rates using a single integrated sensor. This enhanced ACM sensor leverages a nano-gap transduction mechanism to achieve high sensitivity to weak high frequency vibrations occurring on the surface of the skin due to underlying lung pathologies. The performance of the ACM sensor was compared to recordings from a state-of-art digital stethoscope, and the efficacy of the developed system is demonstrated by conducting an exploratory research study aimed at recording pathological mechano-acoustic signals from hospitalized patients with a chronic obstructive pulmonary disease (COPD) exacerbation, pneumonia, and acute decompensated heart failure. This unobtrusive wearable system can enable both episodic and longitudinal evaluation of lung sounds that allow for the early detection and/or ongoing monitoring of pulmonary disease.

Figure 1

ACM sensor and System. (a) Schematic image of ACM design structure with 4 sense electrodes and the proof-mass supported by tether springs at the edges. (b) Fabricated PCB boards housing the ACM sensor and interface electronics. The larger control unit board consists of the data aquation and storage components. (c) Schematic block diagram of components used in the wearable sensor module. (d) image of the packaged wireless sensor system with one ACM sensor head.

Figure 2

Anatomy of the lungs and auscultation sites. The anterior and posterior view of the body illustrating the location of various lung lobes. Areas numbered 1 through 9 indicate the auscultation sites used for data recording from patients. The locations are chosen to examine majority of the lung area during the study.

Figure 3

Comparison of ACM performance with Eko digital stethoscope. (a) Signal waveforms of expiratory wheeze captured using ACM sensor and digital stethoscope indicating a time duration of 250 ms. Signal exhibits sinusoidal characteristic. (b)Signal waveforms of expiratory bronchial breath sounds exhibiting loud, high frequency signals. c Signal waveforms of inspiratory crackle exhibiting short bursts of high frequency signals with a total duration of 180 ms.

Figure 4

Pathological signals recorded from COPD patient. (a) Wheezing lung sound recorded from left upper lobe on the posterior side from patient with COPD. Wheezing periods are highlighted in the waveform. (b) COPD patient exhibiting difficulty in breathing, characterized by a shallow breathing pattern.

Figure 5

Pathological signals recorded from pneumonia patient. (a) Bronchial breath sound recorded from right inferior lobe on the posterior side from patient with pneumonia. Presence of these sounds at peripheral airways in indicative of the disease. (b) Pneumonia patient exhibiting a fast-paced breath rate (27 breaths/min) with a normal breathing pattern.

Figure 6

Pathological signals recorded from ADHF patient. (a) Presence of high frequency inspiratory crackle at lower lobes of the lungs indicating fluid accumulation. (b) Cheyne-Stokes respiration (CSR) pattern recorded from patient with ADHF and is characterized by a period of breathing followed by a period of apnea. CSR is a common indicator of heart failure.