Medical Acoustics

Beach, Kirk W.; Dunmire, Barbrina

doi:10.1007/978-0-387-30425-0_21

Cited by 6 publications

(6 citation statements)

References 69 publications

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“…Ultrasounds can be used for biomedical applications such as imaging and therapy. One of their earliest medical applications was the therapeutic heating of tissue, induced through the absorption of ultrasound, which results in acoustic to thermal energy conversion . At ultrasound intensities lower than that in either thermal ablation or tissue disintegration, slight temperature elevations are achieved, and the treatment is classified as hyperthermia.…”

Section: Introductionmentioning

confidence: 99%

Heating Induced by Therapeutic Ultrasound in the Presence of Magnetic Nanoparticles

Kaczmarek

Hornowski

Kubovčíková

et al. 2018

ACS Appl. Mater. Interfaces

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The efficiency of ultrasound hyperthermia for anti-cancer treatments such as radiotherapy or chemotherapy can be improved by using sonosensitizers, which are materials that enhance the attenuation and dissipation of acoustic energy. We propose the use of magnetic nanoparticles as sonosensitizers because of their biocompatibility, nontoxicity, and common use in several medical applications. A magnetic material was synthetized and then incorporated in the form of a magnetic fluid in agar tissue-mimicking phantoms. Ultrasound hyperthermia studies were conducted at various ultrasound frequencies and concentrations of magnetic nanoparticles in the phantoms. The theoretical modeling based on a heat transfer equation and the experimental results show good agreement and confirm that the temperature rise during ultrasound heating in tissue-mimicking phantoms doped with sonosensitizers is greater than that in a pure agar phantom. Furthermore, on the basis of Pennes' bio-heat equation, which takes into consideration the blood perfusion and metabolic heat, the thermal dose and lesion shapes after sonication were determined for a hypothetical tissue.

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Section: Introductionmentioning

confidence: 99%

Heating Induced by Therapeutic Ultrasound in the Presence of Magnetic Nanoparticles

Kaczmarek

Hornowski

Kubovčíková

et al. 2018

ACS Appl. Mater. Interfaces

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“…Calculation of the Sensitivity. The sensitivity (S) of the acoustic sensor was calculated by S = V P = V P 0 .10 SPL=20 , [1] where P is the sound pressure, V is the peak output voltage of the sensor, and P o is the reference sound pressure of 2 × 10 −5 Pa; the SPL is expressed in dB.…”

Section: Methodsmentioning

confidence: 99%

“…wearable electronics | biomedical devices | mechanoacoustic sensor | gas-permeable sensors E nhancements of acoustic sensor sensitivities have extended their applications into the fields of communications, security, and healthcare/medicine (1)(2)(3)(4)(5)(6)(7)(8). The recent emergence of wearable electronics has provided a strong motivation to further increase the sensitivity of acoustic sensors, particularly in the lowfrequency regime, so as to enable the monitoring of low-intensity body acoustics normally beyond the audible range (1,9). The frequency of heart signals is mainly concentrated in the 10-250-Hz band.…”

mentioning

confidence: 99%

All-nanofiber–based, ultrasensitive, gas-permeable mechanoacoustic sensors for continuous long-term heart monitoring

Nayeem

Lee

Jin

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

146

113

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The prolonged and continuous monitoring of mechanoacoustic heart signals is essential for the early diagnosis of cardiovascular diseases. These bodily acoustics have low intensity and low frequency, and measuring them continuously for long periods requires ultrasensitive, lightweight, gas-permeable mechanoacoustic sensors. Here, we present an all-nanofiber mechanoacoustic sensor, which exhibits a sensitivity as high as 10,050.6 mV Pa−1 in the low-frequency region (<500 Hz). The high sensitivity is achieved by the use of durable and ultrathin (2.5 µm) nanofiber electrode layers enabling a large vibration of the sensor during the application of sound waves. The sensor is ultralightweight, and the overall weight is as small as 5 mg or less. The devices are mechanically robust against bending, and show no degradation in performance even after 1,000-cycle bending. Finally, we demonstrate a continuous long-term (10 h) measurement of heart signals with a signal-to-noise ratio as high as 40.9 decibels (dB).

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“…Interestingly, medical acoustics, i.e. the scientific field using audio signal processing and pattern recognition methods for health diagnosis [1], can play a fundamental role in the development of user-friendly tools to prevent and limit the spread of respiratory diseases [18]. The ability to create automatic methods to detect anomalies is useful for both patients and physicians.…”

Section: Introductionmentioning

confidence: 99%

Variational Autoencoders for Anomaly Detection in Respiratory Sounds

Cozzatti¹,

Simonetta²,

Ntalampiras³

2022

Preprint

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This paper proposes a weakly-supervised machine learningbased approach aiming at a tool to alert patients about possible respiratory diseases. Various types of pathologies may affect the respiratory system, potentially leading to severe diseases and, in certain cases, death. In general, effective prevention practices are considered as major actors towards the improvement of the patient's health condition. The proposed method strives to realize an easily accessible tool for the automatic diagnosis of respiratory diseases. Specifically, the method leverages Variational Autoencoder architectures permitting the usage of training pipelines of limited complexity and relatively small-sized datasets. Importantly, it offers an accuracy of 57%, which is in line with the existing strongly-supervised approaches.

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Medical Acoustics

Cited by 6 publications

References 69 publications

Heating Induced by Therapeutic Ultrasound in the Presence of Magnetic Nanoparticles

Heating Induced by Therapeutic Ultrasound in the Presence of Magnetic Nanoparticles

All-nanofiber–based, ultrasensitive, gas-permeable mechanoacoustic sensors for continuous long-term heart monitoring

Variational Autoencoders for Anomaly Detection in Respiratory Sounds

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