Acoustic Sensor for Voice with Embedded Physiology

Abstract

The Army Research Laboratory (ARL) is developing sensor technology to monitor the soldier's voice and physiology by using enhanced acoustic sensors. The physiological sensor consists of liquid or gel contained within a small, conformable, rubber bladder or pad that also includes a hydrophone. This enables the collection of high signal-to-noise ratio cardiac, respiratory, voice, and other physiological data. The pad also minimizes interference from ambient noise because it couples poorly with airborne noise. It is low cost and comfortable to wear for extended periods. When the sensor pad is in contact with a patient's thorax, neck, or temple region, sounds can be immediately and continuously monitored. This can aid in the remote assessment, diagnosis, and treatment of cardiac and respiratory functions, as well as provide human stress and performance indicators such as heart and breath rates, voice stress, and gross motor indicators. The neck sensor picks up the wearer's voice well, with fidelity sufficient to be used as a hands-free voice activation mechanism using speech recognition software, or for voice communications. The pulse is also detectable from the carotid artery, and excellent breath sounds are present as well. This attachment area is often unobstructed by other equipment or clothing, and is easy to attach quickly to a subject.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1999
Accession Number
ADA390102

Entities

People

  • Michael V. Scanlon

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Biomedical
  • Sensors

DTIC Thesaurus Topics

  • Acoustic Detection
  • Acoustic Detectors
  • Acoustic Impedance
  • Acoustic Properties
  • Acoustics
  • Ambient Noise
  • Arteries
  • Automated Speech Recognition
  • Detection
  • Detectors
  • Health Services
  • Hidden Markov Models
  • Medical Personnel
  • Microphones
  • Physiology
  • Respiration Disorders
  • Word Recognition

Readers

  • Cardiovascular Physiology
  • Sensor Fusion and Tracking Systems.
  • Speech Processing/Speech Recognition.

Technology Areas

  • AI & ML