"Modern ultrasound scanners are portable and have become very useful for clinical diagnosis. However, they have limitations for field use purposes, primarily because they occupy both hands of the physician who performs the scanning. The goal of this thesis is to develop a wearable voice-controlled ultrasound scanner system that would enable the physician to provide a fast and efficient diagnosis. This is expected to become very useful for emergency and trauma applications. A commercially available ultrasound scanner system, Terason 2000, was chosen as the basis for development. This system consists of a laptop, a hardware unit containing the RF beamforming and signal processing chips and the ultrasound transducer. In its commercial version, the control of the ultrasound system is performed via a Graphical User Interface with a Windows-application look and feel. In the system we developed, a command and control speech recognition engine and a noise-canceling microphone are selected to control the scanner using voice commands. A mini-joystick is attached to the top of the ultrasound transducer for distance and area measurements and to perform zooming of the ultrasound images. An eye-wear viewer connected to the laptop enables the user to view the ultrasound images directly. Power management features are incorporated into the ultrasound system in order to conserve the battery power. A wireless connection is set up with a remote laptop to enable real-time transmission of wireless images. The result is a truly untethered, voice-controlled, ultrasound system enclosed in a backpack and monitored by the eye-wear viewer. (In the second generation of this system, the laptop is replaced by an embedded PC and is incorporated into a photographer’s vest). The voice-controlled system has to be made reliable under various forms of background noise. Three command and control speech recognition systems were selected and their recognition performances were determined under different types and levels of ambient noise. The variation of recognition rates was also analyzed over 6 different speakers. A detailed testing was also conducted to identify the ideal combination of a microphone and speech recognition engine suitable for the ultrasound scanner system. Six different microphones, each with their own unique methods of implementing noise cancellation features, were chosen as candidates for this analysis. The testing was conducted by making recordings inside a highly reverberant acoustic noisy chamber, and the recordings were fed to the automatic speech recognition engines offline for performance evaluation. The speech recognition engine and microphone selected as a result of this extensive testing were then incorporated into the wearable ultrasound scanner system. This thesis also discusses the implementation of the human-speech interface, which also plays a major role in the effectiveness of the voice-controlled ultrasound scanner system."