4pBA5 – Plane-wave vector-flow imaging of adult mouse heart

Jeffrey Ketterling– jketterling@riversideresearch.org
Lizzi Center for Biomedical Engineering
Riverside Research
New York, NY 10038

Akshay Shekhar, Orlando Aristizabal
Skirball Institute of Biomolecular Medicine
NYU School of Medicine
New York, NY

Anthony Podkowa
Electrical and Computer Engineering
4251 Beckman Institute MC 251
405 N. Mathews, Urbana Illinois 61801

Billy Y.S. Yiu, Alfred C.H. Yu
Department of Electrical and Computer Engineering
University of Waterloo
Waterloo, ON, Canada

Popular version of paper 4pBA5, “Plane-wave vector-flow imaging of adult mouse heart”
Presented Thursday afternoon, December 6, 2017, 4:30 PM
175th ASA Meeting, Minneapolis

heart

The blood injected in the left ventricle of the mouse heart results in a vortex pattern just as in humans.

Doppler ultrasound is a well established clinical technique to measure blood flow in humans. The method makes use of the Doppler effect to detect small changes in position over time. It is used extensively for cardiovalscular evaluations to detect abnormal blood flow conditions. Traditional Doppler is used either to detect the presence of blood or to assess flow conditions in blood vessels where the flow is more or less steady. Traditional Doppler is only able to assess the flow in the direction normal to the transducer or essentially in the direction that the ultrasound propogates. To estimate the flow velocity that is not in the normal direction, an estimate must be made of the angle between the normal direction and the flow direction. Traditional Doppler is not very effective when trying to image complex flow patterns such as those found in the heart where vortex patterns are formed.

In recent years, advances in ultrasound equipment and computational power have permitted the detection of flow patterns through estimates of local flow vectors using Doppler and other approaches. The methods have been used on humans and the equipment required to perform this type of blood-flow imaging is becoming more widespread and clinical applications are slowly emerging.

Mice are used extensively for cardiovascular studies because many diseases in humans are represented in mouse models. Specialized ultrasound equipment is available to perform Doppler studies on mice. The main difference between the equipment for humans and the equipment for mice is the operating ultrasound frequency. Humans require around 10 MHz frequencies and mice upwards of 20 MHz. Because of this, the vector-flow methods applied to humans have not yet been adapted to imaging mice. The ability to apply the vector-flow approaches to mice would allow for direct translational studies that would facilitate understanding how the complex blood flow patterns in the heart related to healthy heart function.

We undertook initial studies to obtain vector flow information from the left ventricle of a mouse. Data were acquired transmitted ultrasound at an absolute rate of 30,000 frames per second. The effective frame rate after processing was 10,000 frames per second. In terms of flow, the maximum velocity that can be resolved before aliasing in the direction of the ultrasound was 21 cm/s. A video clip [movie] showing 3 hearts cycles, spanning 300 ms, is shown. The flow is indicated by vectors that point in the direction of flow and are colored based on the flow velocity.  Over the heart cycle, the left ventricle can clearly be seen filling via the mitral valve [Fig 1] before developing a vortex pattern [Fig 2] and then the blood is ejected through the aortic valve.

heartFigure 1. Blood flow into the left ventricle through the mitral valve. The flow velocity is near 100 cm/s. Doppler spectrogram from a region near mitral valve. heartFigure 2. After the mitral valve close, a vortex pattern has developed prior to ejection of the blood in the left ventricle.

These initial studies show that the sophisticated methods used to image cardiac mechanics and hemodynamics in humans can be translated to mice. Having similar tools for mice and men will assist in developing applications using vector flow and for understanding fundamental properties of cardiovascular function as they relate to blood flow, mechanics and the related forces between the two. 

This movie shows several heart cycles and the blood flow patterns.

[1] B. Y. S. Yiu and A. C. H. Yu, “Least-squares multi-angle Doppler estimators for plane wave vector flow imaging.” IEEE Trans Ultrason Ferroelectr Freq Control, vol. 63, no. 11, pp. 1733–1744, 2016.

[2] 2.  J.A. Ketterling, O. Aristizábal, B.Y.S. Yiu, D.H. Turnbull, C.K.L. Phoon, A.C.H. Yu and R.H. Silverman, “High-speed, high-frequency ultrasound,  in utero vector-flow imaging of mouse embryos,” Scientific Reports, 7, 16558 (2017)

5aPA – A Robust Smartphone Based Multi-Channel Dynamic-Range Audio Compression for Hearing Aids

Yiya Hao– yxh133130@utdallas.edu
Ziyan Zou – ziyan.zou@utdallas.edu
Dr. Issa M S Panahi – imp015000@utdallas.edu

Statistical Signal Processing Laboratory (SSPRL)
The University of Texas at Dallas
800W Campbell Road, Richardson, TX – 75080, USA

Popular Version of Paper 5aPA, “A Robust Smartphone Based Multi-Channel Dynamic-Range Audio Compression for Hearing Aids”
Presented Friday morning, May 11, 2018, 10:15 – 10:30 AM, GREENWAY J
175th ASA Meeting, Minneapolis

Records by National Institute on Deafness and Other Communication Disorders (NIDCD) indicate that nearly 15% of adults (37 million) aged 18 and over report some kind of hearing loss in the United States. Amongst the entire world population, 360 million people suffer from hearing loss.

Hearing impairment degrades perception of speech and audio signals due to low frequency- dependent audible threshold levels. Hearing aid devices (HADs) apply prescription gains and dynamic-range compression for improving users’ audibility without increasing the sound loudness to uncomfortable levels. Multi-Channel dynamic-range compression enhances quality and intelligibility of audio output by targeting each frequency band with different compression parameters such as compression ratio (CR), attack time (AT) and release time (RT).

Increasing the number of compression channels can result in more comfortable audio output when appropriate parameters are defined for each channel. However, the use of more channels increases computational complexity of the multi-channel compression algorithm limiting its application to some HADs. In this paper, we propose a nine-channel dynamic-range compression (DRC) with an optimized structure capable of running on smartphones and other portable digital platforms in real time. Test results showing the performance of proposed method are presented too. The block diagram of proposed method shows in Fig.1. And the block diagram of compressor shows in the Fig.2.

Fig.1. Block Diagram of 9-Channel Dynamic-Range Audio Compression

Fig.2. Block Diagram of Compressor

Several experimental results have been measured including the processing time measurements of real-time implementation of proposed method on an Android smartphone, objective evaluations and subjective evaluations, a commercial audio compression & limiter provided by Hotto Engineering [1] is used as a comparison running on a laptop. Proposed method running on a Google Pixel smartphone with operating system 6.0.1. The sampling rate is set to 16kHz and the frame size is set as 10 ms.

The High-quality INT eractomes (HINT) sentences database at 16 kHz sampling rate are used. First experimental measurement is testing the processing time running on the smartphone. Two processing times were measured, round-trip latency and algorithms processing time. Larsen test was used to measure the round-trip latency [2], and the test setup shows in Fig.3. The average processing time results shows in Fig.2 as well. Perceptual evaluation of speech quality (PESQ) [3] and short-time objective intelligibility (STOI) [4] has been used to test the objective quality and intelligibility of proposed nine-channel DRC.

The results could be find in Fig.4. Subjective tests including mean opinion score (MOS) test [5] and word recognition test (WR) have been tested, and the Fig.5 shows the results. Based on the results we can tell that proposed nine-channel DRC could run on the smartphone efficiently, and provides with decent quality and intelligibility as well.

Fig.3. Processing Time Measurements and Results

Fig.4. Objective evaluation results of speech quality and intelligibility.

Fig.5. Subjective evaluation results of speech quality and intelligibility.

Based on the results we can tell, proposed nine-channel dynamic-range audio compression could provide with decent the quality and intelligibility which could run on smartphones. Proposed DRC could pre-set all the parameters based on the audiograms of individuals. With proposed compression, the multi-channel DRC does not limit within advanced hardware, which is costly such as hearing aids or laptops. Proposed method also provides with a portable audio framework, which not just limiting in current version of DRC, but could be extended or upgraded further for research study.

Please refer our lab website http://www.utdallas.edu/ssprl/hearing-aid-project/ for video demos and the sample audio files are as attached below.

Audio files:

Unprocessed_MaleSpeech.wav

Unprocessed_FemaleSpeech.wav

Unprocessed_Song.wav

Processed_MaleSpeech.wav

Processed_FemaleSpeech.wav

Processed_Song.wav

Key References:

  • 2018. [Online]. Available: http://www.hotto.de/
  • 2018. [Online]. Available: https://source.android.com/devices/audio/latency_measurements
  • Rix, W., J. G. Beerends J.G., Hollier, M. P., Hekstra, A. P., “Perceptual evaluation of speech quality (PESQ) – a new method for speech quality assessment of telephone networks and codecs,” IEEE Int. Conf. Acoust., Speech, Signal Processing (ICASSP), 2, pp. 749-752., May 2001.
  • Tall, C. H, Hendricks, R. C., Heusdens, R., Jensen, R., “An algorithm for intelligibility prediction of time-frequency weighted noisy speech,” IEEE trans. Audio, Speech, Lang. Process. 19(7), pp. 2125- 2136., Feb
  • Streijl, R. C., Winkler, S., Hands, D. S., “Mean opinion score (MOS) revisited: methods and applications, limitations and alternatives,” in Multimedia Systems 22.2, pp. 213-227, 2016.

*This work was supported by the National Institute of the Deafness and Other Communication Disorders (NIDCD) of the National Institutes of Health (NIH) under the grant number 5R01DC015430-02. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The authors are with the Statistical Signal Processing Research Laboratory (SSPRL), Department of Electrical and Computer Engineering, The University of Texas at Dallas.

2pBA5 – Sensing Osteoporosis by Acoustic Waves of Ultrasound

Siavash Ghavami – roudsari.seyed@mayo.edu
Max Denis – denis.max@mayo.edu
Adriana Gregory – gregory.adriana@mayo.edu
Jeremy Webb – webb.jeremy@mayo.edu
Mahdi Bayat – bayat.mahdi@mayo.edu
Mostafa Fatemi – fatemi.mostafa@mayo.edu
Azra Alizad – alizad.azra@mayo.edu

Mayo Clinic, College of Medicine and Science,
Department of Radiology, Department of Physiology and Biomedical Engineering
200 1st St SW, Rochester, MN 55905, USA

Popular version of paper 2pBA5, “Vibro-Acoustic Method for Detection of Osteopenia and Osteoporosis”
Presented Tuseday afternoon, May 8, 2018, 2:15-2:30 PM, GREENWAY F/G
175th ASA Meeting, Minneapolis

Osteoporosis, a condition with low bone mass and micro-architectural deterioration, is the most common bone disease in adults that leads to skeletal fragility and increased risk of fracture. Age-related osteoporosis is by far the most common form of the disease, most commonly in women after menopause and older men. Osteopenia refers to bone density that is lower than normal peak density, but not low enough to be classified as osteoporosis. Bone density is a measurement of how dense and strong the bones are. If the bone density is low compared to the normal peak density, the bone is said to have osteopenia. Having osteopenia means there is a greater risk that, as time passes, it may develop bone density that is very low compared to normal, known as osteoporosis.

Assessment of bone mass and bone quality is essential for early detection of osteopenia and osteoporosis in people at risk as well as for monitoring the efficacy of various therapeutic regimens projected to reduce fractures associated with these diseases. Estimations of bone mineral density (BMD) and double energy X-ray absorptiometry (DXA) have played an important role in bone evaluation and prediction of fractures risks in recent years. Although DXA is now the gold standard for bone mass measurements in adults, this method uses x-ray which can be harmful especially if used repeatedly.

In this study, a new noninvasive method is proposed for detection of osteoporosis and osteopenia. In this method a pulse of ultrasound is used to induces vibrations in the bone, where these vibrations produce an acoustic wave that is measured by a sensitive hydrophone placed on the skin. The resulting acoustic signals are used to measure wave velocity in the bone, which in turn used to assess the bone quality. The accuracy of wave velocity estimation in the bone is affected by the complex acoustic environment. The acoustic wave in this environment can be thought of as a composition of several simpler wave components. We used an efficient technique to decompose received signal into constructing components. This allowed us to choose the wave component that represents bone vibration. Using this component we estimate wave velocity in the bone and used it to decide about the bone abnormality.

The study was done on 27 volunteers, out of those 8 had osteopenia, 6 had osteoprosis, and 13 were healthy with no bone abnormality. For each volunteer the right and left tibia (the long bone in lower leg) were tested. By comparing the wave velocities, we were able to correctly identify those osteoporosis and osteopenia from healthy individual in up to 89% of the cases. This technique can provide physicians a safe, low-cost, and portable tool for diagnosis of osteoporosis and osteopenia in patients.

Osteoporosis

Fig. 1. Estimated wave velocity in osteopenic osteoporotic and normal bones.

3aAA7 – Fast and perceptually convincing simulation of room acoustics: Shoebox rooms with bells and whistles

Oliver Buttler – oliver.buttler@uni-oldenburg.de
Torben Wendt – torben.wendt@uni-oldenburg.de
Steven van de Par – steven.van.de.par@uni-oldenburg.de
Stephan D. Ewert – stephan.ewert@uni-oldenburg.de

Medical Physics and Acoustics and Cluster of Excellence Hearing4all,
University Oldenburg
Carl-von-Ossietzky-Straße 9-11
26129 Oldenburg, GERMANY

Popular version of paper 3aAA7, “Perceptually plausible room acoustics simulation including diffuse reflections”
Presented Wednesday morning, May 9, 2018, 10:50-11:05 AM, Location: NICOLLET C
175th ASA Meeting, Minneapolis

Today’s audio technology allows us to create virtual environments where the listener feels immersed in the scene. This technology is currently used in entertainment, computer games, but also in research where the function of a hearing aid algorithm or the behavior of humans in complex and realistic situations is investigated. To create such immersive virtual environments, besides convincing computer graphics also convincing computer sound is of key importance. We can easily experience the richness of the acoustic world when we close our eyes. We can hear that the acoustic world allows us to perceive sounds in an omnidirectional way such that we can perceive a sound source from different directions or even around a corner, and we might even be able to hear whether we are in a concert hall or bathroom, based on the acoustics.

To create immersive and convincing acoustics in virtual reality applications, computationally efficient methods are required. While in the last decades, the development towards today’s astonishing real-time computer graphics was strongly driven by the first-person computer game genre, until recently, comparable techniques in computer sound received much less attention. One reason might be that the physics of sound propagation and acoustics is at least as complicated as that of light propagation and illumination, and computing power was mainly spent on computer graphics so far. Moreover, from early on, computer graphics focused on the creation of visually convincing results rather than on physics-based simulation which allowed for tremendous simplifications of the computations. Methods for simulating acoustics, however, often focused on physics-based to predict how a planned concert hall or classroom might sound like. These methods disregarded perceptual limitations of our hearing system that might allow for significant simplifications of the acoustic simulations.

Our perceptually plausible room acoustics simulator [RAZR, www.razrengine.com, 1]  creates a computationally efficient acoustics simulation by drastic simplifications with respect to physical accuracy while still accomplishing a perceptually convincing result. To achieve this, RAZR approximates the geometry of real rooms by a simple, empty shoebox-shaped room and calculates the first sound reflections from walls as if they were mirrors creating image sources for a sound source in the room [2]. Later reflections that we perceive as reverb are treated in an even more simplified way and only the temporal decay of sound energy and the binaural distribution at our two ears is considered using a so-called feedback-delay-network [FDN, 3].

Although we demonstrated that a good perceptual agreement with real non-shoebox rooms is indeed achieved [1], the empty shoebox-room simplification might be too inaccurate for rooms which strongly diverge from this assumption, e.g., a staircase or a room with multiple interior objects. Here multiple reflections and scattering occur which we simulate in a  perceptually convincing manner by temporal smearing of the simulated reflections. A single parameter was introduced to quantify deviations from an empty shoebox room and thus the amount of temporal smearing. We demonstrate that a perceptually convincing room acoustical simulation can be obtained for sounds like music and impulses similar to a hand clap. Given its tremendous simplifications, we believe that RAZR is optimally suited for real-time acoustics simulation even in mobile devices were virtual sounds could be embedded in augmented reality applications.

 Shoebox rooms
Figure 1. Examples for the simplification of different real room geometries to shoeboxes in RAZR. The red boxes indicate the shoebox approximation. The green box in panel c) indicates a second, coupled volume attached to the lower main volume. While the rooms in panel a) and b) might be well approximated with the empty shoebox, the rooms in panel c) and d) show more severe deviations which were accounted for by a single parameter estimating the deviation from the shoebox in percent and by applying the according temporal smearing to the reflections.

 
Figure 2. Perceptually rated differences between real room recordings (A: large aula, C: corridor, S: seminar room) and simulated rooms with a hand-clap-like sound source (pulse). Different perceptual attributes are shown in the panels. The error bars indicate inter-subject standard deviations. Depending on the attribute, ordinate scales range from “less pronounced” to “more pronounced” or semantically fitting descriptors. The different symbols show the amount of deviation from the empty shoebox assumption as percentage. It can be seen that with a deviation of 20% the critical attributes in the lower panel are rated near zero and thus show a good correspondence with the real room. The remaining overall difference is mainly caused by differences in tone color which can be easily addressed.

 
Figure 3. The virtual audio-visual environment lab at the University of Oldenburg features 86 loudspeakers and 8 subwoofers arranged in a full spherical setup to render 3-dimensional simulated sound fields. The foam wedges at the walls create an anechoic environment, so that the sound created by the loudspeakers is not affected by unwanted sound reflections at the walls.

Sound 1. Simulation of the large aula without the assumption of interior objects and multiple sound reflections on those objects. Although the sound is not distorted, an unnatural and crackling sound impression is obvious at the beginning.

Sound 2. Simulation of the large aula with the assumption of 20% of the empty space filled with objects. The sound is more natural and the crackling impression at the beginning is gone.

[1] T. Wendt, S. Van De Par, and S. D. Ewert, “A computationally-efficient and perceptually-plausible algorithm for binaural room impulse response simulation,” Journal of the Audio Engineering Society, 62(11):748–766, 2014.

[2] J. B. Allen and D. A. Berkley, “Image method for efficiently simulating small-room acoustics,” The Journal of the Acoustical Society of America, 65(4):943–950, 1979.

[3] J.-M. Jot and A. Chaigne, “Digital delay networks for designing artificial reverberators,” In 90th Audio Engineering Society Convention, Audio Engineering Society, 1991.

1aAO5 – Underwater sound from recreational swimmers, divers, surfers, and kayakers


Christine Erbe – Curtin University, c.erbe@curtin.edu.au
Miles Parsons – Curtin University and Australian Institute of Marine Science, m.parsons@aims.gov.au
Alec Duncan – Curtin University, A.J.Duncan@curtin.edu.au
Klaus Lucke – Curtin University and JASCO Applied Sciences, Klaus.lucke@jasco.com
Alexander Gavrilov – Curtin University, A.Gavrilov@curtin.edu.au
Kim Allen – THHINK Autonomous Systems, kim.allen@thhink.com

Centre for Marine Science & Technology, Curtin University, Bentley, 6102 Western Australia, AUSTRALIA|

Popular version of paper 1aAO5
Presented Monday morning, May 7, 2018, 11:10-11:25 a.m., GREENWAY A
175th ASA Meeting, Minneapolis, MN

Underwater sound contains a lot of information about the source that produces it. Ships, for example, have a characteristic sound signature underwater, by which the type of vessel, its speed, and its route can easily be determined. In some cases, individual vessels can be identified by their sound and information about the type of propulsion, operational mode, and load can be deduced and maintenance issues (e.g., relating to the propeller) can be picked out. Similarly, just by listening, we can study marine life from whales to fishes and shrimp; we can track their movements; monitor their behavior; and in the case of some species of dolphins, even say which family and individuals are there. Sound is an important commodity for marine life; marine mammals as well as fishes, for example, communicate through sound, sense their environment, navigate, and forage—all mediated by sound.

Video 1: Underwater video and sound recording of different water sports activities.

Given the important role sound plays in the life functions of marine fauna, the potential interference by man-made noise has received growing interest. Noise may disrupt animal behavior, affect their hearing abilities, mask communication, cause stress, and in extreme cases cause physical and physiological damage that can ultimately be fatal. The research and management focus has—quite sensibly—been on the strongest sources, such as geophysical surveys or coastal and marine construction. Non-motorised activities are expected quieter and have hardly been studied.

Within the framework of an underwater acoustic project, we had the opportunity to record ourselves and friends performing a number of recreational water sports activities in a quiet Olympic pool, with all surrounding machinery (including cleaning pumps) switched off [1,2]. Specifically, different people were filmed and acoustically recorded while swimming breaststroke, backstroke, freestyle, and butterfly; snorkeling with and without fins; paddling a surfboard with alternating single or double arms; scuba diving; kayaking; and jumping into the pool. Sound pressure and water particle velocity were measured.

Activities that occurred at the surface, involved repeatedly piercing the surface and hence created bubble clouds were the strongest sound generators. Received levels were 110-131 dB re 1 µPa (10-16,000 Hz) for all of the activities at the closest point of approach (1 m). Levels were lower than those found in environmental noise regulations, but were clearly above ambient noise levels recorded off beaches and hence predicted audible by marine fauna over tens to hundreds of meters.

The characterization and quantification of underwater sound from recreational water sports has applicability well beyond environmental management. For example, just by listening to the recordings, it is easy to identify who of the volunteers was in the pool and which activity (including which style of swimming, with or without fins, with single versus double arms, etc.) was performed. The better (i.e., faster and smoother) swimmers were the quieter swimmers. Underwater sound might be a useful tool to assess professional or competitive swimmer performance and can be used for security monitoring of pools.

[1] C. Erbe, M. Parsons, A. J. Duncan, K. Lucke, A. Gavrilov and K. Allen, “Underwater particle motion (acceleration, velocity and displacement) from recreational swimmers, divers, surfers and kayakers,” Acoustics Australia 45,  293-299 (2017). doi: 10.1007/s40857-017-0107-6

[2] C. Erbe, M. Parsons, A. J. Duncan and K. Allen, “Underwater acoustic signatures of recreational swimmers, divers, surfers and kayakers,” Acoustics Australia 44 (2),  333-341 (2016). doi: 10.1007/s40857-016-0062-7