Diffuse brain injury (DBI) commonly results from blunt impact followed by sudden head rotation, wherein severity is a function of rotational kinematics. A noninvasive in vivo rat model was designed to further investigate this relationship. Due to brain mass differences between rats and humans, rotational acceleration magnitude indicative of rat DBI ( approximately 350 krad/s(2)) has been estimated as approximately 60 times greater than that of human DBI ( approximately 6 krad/s(2)). Prior experimental testing attempted to use standard transducers such as linear accelerometers to measure loading kinematics. However, such measurement techniques were intrusive to experimental model operation. Therefore, initial studies using this experimental model obtained rotational displacement data from videographic images and implemented a finite difference differentiation (FDD) method to obtain rotational velocity and acceleration. Unfortunately, this method amplified high-frequency, low-amplitude noise, which interfered with signal magnitude representation. Therefore, a coherent average technique was implemented to improve the measurement of rotational kinematics from videographic images, and its results were compared with those of the previous FDD method. Results demonstrated that the coherent method accurately determined a low-pass filter cutoff frequency specific to pulse characteristics. Furthermore, noise interference and signal attenuation were minimized compared with the FDD technique.

Download full-text PDF

Source
http://dx.doi.org/10.1115/1.3078182DOI Listing

Publication Analysis

Top Keywords

low-pass filter
8
filter cutoff
8
rotational kinematics
8
experimental model
8
videographic images
8
fdd method
8
rotational
5
determination low-pass
4
cutoff frequencies
4
frequencies high-rate
4

Similar Publications

Quantum technology exploits fragile quantum electronic phenomena whose energy scales demand ultra-low electron temperature operation. The lack of electron-phonon coupling at cryogenic temperatures makes cooling the electrons down to a few tens of millikelvin a non-trivial task, requiring extensive efforts on thermalization and filtering high-frequency noise. Existing techniques employ bulky and heavy cryogenic metal-powder filters, which prove ineffective at sub-GHz frequency regimes and unsuitable for high-density quantum circuits such as spin qubits.

View Article and Find Full Text PDF

Extracting speech spectrogram of speech signal based on generalized S-transform.

PLoS One

January 2025

College of Computer Science and Technology, Xinjiang University, Urumqi, Xinjiang, China.

In speech signal processing, time-frequency analysis is commonly employed to extract the spectrogram of speech signals. While many algorithms exist to achieve this with high-quality results, they often lack the flexibility to adjust the resolution of the extracted spectrograms. However, applications such as speech recognition and speech separation frequently require spectrograms of varying resolutions.

View Article and Find Full Text PDF

Objectives: To investigate the influence of frequency-specific audibility on audiovisual benefit in children, this study examined the impact of high- and low-pass acoustic filtering on auditory-only and audiovisual word and sentence recognition in children with typical hearing. Previous studies show that visual speech provides greater access to consonant place of articulation than other consonant features and that low-pass filtering has a strong impact on perception on acoustic consonant place of articulation. This suggests visual speech may be particularly useful when acoustic speech is low-pass filtered because it provides complementary information about consonant place of articulation.

View Article and Find Full Text PDF

Human-machine interfaces and wearable electronics, as fundamentals to achieve human-machine interactions, are becoming increasingly essential in the era of the Internet of Things. However, contemporary wearable sensors based on resistive and capacitive mechanisms demand an external power, impeding them from extensive and diverse deployment. Herein, a smart wearable system is developed encompassing five arch-structured self-powered triboelectric sensors, a five-channel data acquisition unit to collect finger bending signals, and an artificial intelligence (AI) methodology, specifically a long short-term memory (LSTM) network, to recognize signal patterns.

View Article and Find Full Text PDF

Purpose: The background of this scoping review is that pediatric neurosurgery in the vicinity of motor pathways is associated with the risk of motor tract damage. By measuring transcranial electrical evoked potentials in muscles (electromyogram) or from the spinal cord (epidural D-wave) functional disorders and impending damage can be detected during surgery and countermeasures can be initiated. The objective was to summarize stimulation techniques of transcranial electrical stimulation and the success rate of motor evoked potentials exclusively in children undergoing neurosurgery.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!