1pNS1 – Acoustic vehicle alerts and sleep disruption: A content analysis of online discussion forums – Jeanine Botta

Acoustic vehicle alerts and sleep disruption: A content analysis of online discussion forums

Jeanine Botta – jeanine.botta@downstate.edu
The Right to Quiet Society for Soundscape Awareness and Protection
720 East 31st Street
Apartment 7G
Brooklyn, NY 11210

Popular version of paper 1pNS1
Presented Monday afternoon, May 13, 2019
177th ASA Meeting, Louisville, KY

Based on quieter engines that have evolved over decades with electric, hybrid, and many internal combustion engine vehicles, authoritative voices tell us that the problem of noisy cars has been solved. Moving vehicles may be quieter now, but this is not the case for cars that are stationary.

Most vehicles manufactured for the North American market feature an audible signal that assures owners that they have locked their cars. Roughly half of cars sold in the U.S. and Canada use an electronic tone, while the rest use a horn sound. Most cars offer the option to use a visual signal.

Owners can lock a car and arm its security system without use of any signal, but this feature is rarely discussed when buying a car. With some cars, remote start, stages of battery charging, and stages of filling a tire with air use a horn signal. Some brands have incorporated horn sounds to signify that the engine is running when its driver has left the car.

Many people are unaware of acoustic vehicle signals, or the fact that some horn sounds are emitted from parked cars. Awareness may occur after buying a car or when walking in front of a car that is being locked. When one’s home faces a parking lot or street parking, sleep disruption can occur, and annoyance can affect the ability to return to sleep.

This study was conducted to explore common experiences related to sleep disruption caused by remote horn signaling, using content analysis of online complaints posted in discussion forums and forums created by car owners who want to disable the sound. The study uses a database that was compiled as part of a noise activism endeavor called the Silence the Horns project.

In complaint forum posts, remote horn signals are described as a source of sleep disruption, reduced quality of life, annoyance, and emotional and physical stress responses. Other concerns include hearing health, safety, and legal considerations. Posts can provide useful information, even as some authors introduce a degree of antagonism. [1]

Car owner forum posts are practical. Authors may not mention a reason for wanting to eliminate the horn sound, but when they do, concerns include general consideration for neighbors, specific concerns about sleep disruption of a family member or neighbor, and embarrassment about creating a sound that brings attention. Authors are helpful, often post in other auto topic forums, and set a friendly tone. [2]

Online forum data will continue to be added to the database throughout 2019. It is hoped that auto industry stakeholders might consider sleep disruption to be an important unintended consequence of horn use with lock confirmation in future car models.

If passed, proposed Senate bill S.543, the Protecting Americans from the Risks of Keyless Ignition Technology Act, would protect consumers from the risk of carbon monoxide poisoning related to cars inadvertently left with the engine running. [3, 4] Stakeholders should be aware that consumers are eliminating horn sounds that automakers implemented to discourage leaving a car with the engine running.


[1] ParaPundit forum, Locking A Car With A Short Horn Blast Is Rude and Obnoxious

[2] GM-VOLT: Chevy Volt Electric Car Site, Suppress option for Charging Honk

[3] Blumenthal announces legislation to protect against CO and rollaway risk raised by keyless cars

[4] S.543 – PARK IT Act

1pBA11 – An ultrasound surface wave elastography technique for noninvasive measurement of scar tissue – Boran Zhou

“An ultrasound surface wave elastography technique for noninvasive measurement of scar tissue”

Boran Zhou – zhou.boran@mayo.edu
Xiaoming Zhang – zhang.xiaoming@mayo.edu
Department of Radiology, Mayo Clinic,
Rochester, MN 55905 

Saranya P. Wyles – Wyles.Saranya@mayo.edu
Alexander Meves – Meves.Alexander@mayo.edu
Department of Dermatology, Mayo Clinic,
Rochester, MN 55905 

Steven Moran – Moran.Steven@mayo.edu
Department of Plastic Surgery, Mayo Clinic,
Rochester, MN 55905

Popular version of paper 1pBA11
Presented Monday afternoon, May 13, 2019
177th ASA Meeting, Louisville, KY

Hypertrophic scars and keloids are characterized by excessive fibrosis and can be functionally problematic. Indeed, hypertrophic scarring is characterized by wide, raised scars that remain within the original borders of injury and have a rapid growth phase. We have developed an ultrasound elastography technique to assess the skin elasticity for patients with scleroderma (1). Currently, no clinical technique is available to noninvasively quantify and assess the progression and development of scar restoration. There is a need for quantitative scar measurement modalities to effectively evaluate and monitor treatments.

We aim to assess the role of ultrasound surface wave elastography (USWE) in accurately evaluating scar metrics. 3 Patients were enrolled in this research based on their clinical diagnoses. For the patients with scar on the forearm, they were tested in a sitting position with their left or right forearm or upper arm placed horizontally on a pillow in a relaxed state. The indenter of the handheld shaker was placed on the tissue at control and scar sites. A 0.1-s harmonic vibration was generated by the indenter on the tissue (2). The vibration was generated at 3 frequencies: 100, 150 and 200 Hz. An ultrasound system with an ultrasound probe with a central frequency of 6.4 MHz was positioned about 5 mm away from the indenter and used for detecting the surface wave motion of the tissue (3).

The wave motions on the 8 selected locations on the tissue surface were noninvasively measured using our ultrasound-based method (Fig. 1a)(4). The phase change with distance of the harmonic wave propagation on the tissue surface was used to measure the surface wave speed.
The measurement of wave speed can be improved by using multiple phase change measurements over distances (5). The regression of the phase change with distance can be obtained by “best fitting” a linear relationship between them (Fig. 1b). Using the tissue motion at the first location as a reference, the wave phase delay of the tissue motions at the remaining locations, relative to the first location, was used to measure surface wave speed (6).

Wave speeds of forearm or upper arm control and scar sites of the 3 patients at 100, 150, and 200 Hz before and after treatment were compared in Figure 2. The p values for the t-tests of the differences between before and after treatment were less than 0.05 for scar sites at 3 frequencies. The higher wave speed indicates the stiffer tissue. The obtained results suggest that scar portion was softener after treatment. USWE provides an objective assessment of the reaction of the scar to injury and treatment response.

Figure 1. (a) Representative B-mode image of skin, (b) Blue circles represent the selected dots for wave speed measurement.

Figure 2. Comparison of wave speeds at 3 frequencies between forearm control and scar sites.


1. Zhang X, Zhou B, Kalra S, Bartholmai B, Greenleaf J, Osborn T. An Ultrasound Surface Wave Technique for Assessing Skin and Lung Diseases. Ultrasound in Medicine & Biology. 2018;44(2):321-31.
2. Zhang X, Osborn T, Zhou B, et al. Lung ultrasound surface wave elastography: a pilot clinical study. IEEE transactions on ultrasonics, ferroelectrics, and frequency control. 2017;64(9):1298-304.
3. Clay R, Bartholmai BJ, Zhou B, et al. Assessment of Interstitial Lung Disease Using Lung Ultrasound Surface Wave Elastography: A Novel Technique With Clinicoradiologic Correlates. J Thorac Imaging. 2018.
4. Zhang X, Zhou B, Miranda AF, Trost LW. A Novel Noninvasive Ultrasound Vibro-elastography Technique for Assessing Patients With Erectile Dysfunction and Peyronie Disease. Urology. 2018;116:99-105.
5. Zhou B, Zhang X. The effect of pleural fluid layers on lung surface wave speed measurement: Experimental and numerical studies on a sponge lung phantom. Journal of the Mechanical Behavior of Biomedical Materials. 2019;89:13-8.
6. Zhang X, Zhou B, Osborn T, Bartholmai B, Kalra S. Lung ultrasound surface wave elastography for assessing interstitial lung disease. IEEE Transactions on Biomedical Engineering. 2018:1-.

5aAB4 – How far away can an insect as tiny as a female mosquito hear the males in a mating swarm? – Lionel Feugère

How far away can an insect as tiny as a female mosquito hear the males in a mating swarm?

Lionel Feugère1,2 – l.feugere@gre.ac.uk
Gabriella Gibson2 – g.gibson@gre.ac.uk
Olivier Roux1 – olivier.roux@ird.fr
Université de Montpellier,
Montpellier, France.
2Natural Resources Institute,
University of Greenwich,
Chatham, Kent ME4 4TB, UK.

Popular version of paper 5aAB4
Presented Friday morning during the session “Understanding Animal Song” (8:00 AM – 9:30 AM), May 17, 2019

177th ASA Meeting, Louisville, KY

Why do mosquitoes make that annoying sound just when we are ready for a peaceful sleep? Why do they risk their lives by ‘singing’ so loudly? Scientists recently discovered that mosquito wing-flapping creates tones that are very important for mating; the flight tones help both males and females locate a mate in the dark.

Mosquitoes hear with their two hairy antennae, which vibrate when stimulated by the sound-wave created by another mosquito flying nearby. Their extremely sensitive hearing organ at the base of the antennae transforms the vibrations into an electrical signal to the brain, similar to how a joystick responds to our hand movements. Mosquitoes have the most sensitive hearing of all insects, however, this hearing mechanism is optimal only at short distances. Consequently, scientists have assumed that mosquitoes use sound for only very short-range communication.

Theoretically, however, a mosquito can hear a sound at any distance, provided it is loud enough. In practice, a single mosquito will struggle to hear another mosquito more than a few centimeters away because the flight tone is not loud enough. However, in the field mosquitoes are exposed to much louder flight tones. For example, males of the malaria mosquito, Anopheles coluzzii, can gather by the thousands in station-keeping flight (‘mating swarms’) for at least 20 minutes at dusk, waiting for females to arrive. We wondered if a female mosquito could hear the sound of a male swarm from far away if the swarm is large enough.

To investigate this hypothesis, we started a laboratory population of An. gambiae from field-caught mosquitoes and observed their behaviour under field-like environmental conditions in a sound-proof room. Phase 1: we reproduced the visual cues and dusk lighting conditions that trigger swarming behaviour, and released males in groups of tens to hundreds of males and recorded their flight-sounds (listen to SOUND 1). 

Phase 2: we released one female at a time and played-back the recordings of different sizes of male swarms over a range of distances to determine how far away a female can detect males. If a female hears a flying male or males, she alters her own flight tone to let the male(s) know she is there.

Our results show that a female cannot hear a small swarm until she comes within tens of centimeter of the swarm. However, for larger, louder swarms, females consistently responded to male flight tones. The larger the number of males in the swarm, the further away the females responded; females detected a swarm of ~1,500 males at a distance of ~0.75 m, and they detected a swarm of ~6,000 males at a distance of ~1.5 m.

2aSPa8 and 4aSP6 – Safe and Sound – Using acoustics to improve the safety of autonomous vehicles – Eoin A King

Safe and Sound – Using acoustics to improve the safety of autonomous vehicles

Eoin A King – eoking@hartford.edu
Akin Tatoglu
Digno Iglesias
Anthony Matriss
Ethan Wagner

Department of Mechanical Engineering
University of Hartford
200 Bloomfield Avenue
West Hartford, CT 06117

Popular version of papers 2aSPa8 and 4aSP6
Presented Tuesday and Thursday morning, May 14 & 16, 2019
177th ASA Meeting, Louisville, KY


In cities across the world everyday, people use and process acoustic alerts to safely interact in and amongst traffic; drivers listen for emergency sirens from police cars or fire engines, or the sounding of a horn to warn of an impending collision, while pedestrians listen for cars when crossing a road – a city is full of sounds with meaning, and these sounds make the city a safer place.

Future cities will see the large-scale deployment of (semi-) autonomous vehicles (AVs). AV technology is quickly becoming a reality, however, the manner in which AVs and other vehicles will coexist and communicate with one another is still unclear, especially during the prolonged period of mixed vehicles sharing the road. In particular, the manner in which Autonomous Vehicles can use acoustic cues to supplement their decision-making process is an area that needs development.

The research presented here aims to identify the meaning behind specific sounds in a city related to safety. We are developing methodologies to recognize and locate acoustic alerts in cities and use this information to inform the decision-making process of all road users, with particular emphasis on Autonomous Vehicles. Initially we aim to define a new set of audio-visual detection and localization tools to identify the location of a rapidly approaching emergency vehicle. In short we are trying to develop the ‘ears’ to complement the ‘eyes’ already present on autonomous vehicles.

Test Set-Up
For our initial tests we developed a low cost array consisting of two linear arrays of 4 MEMS microphones. The array was used in conjunction with a mobile robot equipped with visual sensors as shown in Fig. 1. Our array acquired acoustic signals that were analyzed to i) identify the presence of an emergency siren, and then ii) determine the location of the sound source (which was occasionally behind an obstacle). Initially our tests were conducted in the controlled setting of an anechoic chamber.

Picture 1: Test Robot with Acoustic Array

Step 1: Using convolutional neural networks for the detection of an emergency siren

Using advanced machine learning techniques, it has become possible to ‘teach’ a machine (or a vehicle) to recognize certain sounds. We used a deep layer Convolutional Neural Network (CNN) and trained it to recognize emergency sirens in real time, with 99.5% accuracy in test audio signals.

Step 2: Identifying the location of the source of the emergency siren

Once an emergency sound has been detected, it must be rapidly localized. This is a complex task in a city environment, due to moving sources, reflections from buildings, other noise sources, etc. However, by combining acoustic results with information acquired from the visual sensors already present on an autonomous vehicle, it will be possible to identify the location of a sound source. In our research, we modified an existing direction-of-arrival algorithm to report a number of sound source directions, arising from multiple reflections in the environment (i.e. every reflection is recognized as an individual source). These results can be combined with the 3D map of the area acquired from the robot’s visual sensors. A reverse ray tracing approach can then be used to triangulate the likely position of the source.

Picture 2: Example test results. Note in this test our array indicates a source at approximately 30o and another at approximately -60o.

Picture 3: Ray Trace Method. Note, by tracing the path of the estimated angles, both reflected and direct, the approximate source location can be triangulated.

Video explaining theory.