scholarly journals Musical Information Visualization System

2021 ◽  
Vol 4 (4) ◽  
Author(s):  
Roman O. Yaroshenko
Keyword(s):  
Real Time ◽  
Information Visualization ◽  
Frequency Analysis ◽  
Spectral Composition ◽  
Audio Signal ◽  
Signal Spectrum ◽  
Time Data ◽  
Visualization System ◽  
Music Information ◽  
Led Matrix

The visualisation systems are spread widely as personal computer’s software. The system, that are processing audio data are presented in this article. The system visualizes the ratio of spectrum amplitudes and has fixed frequency binding to colours. The technology of audio signals processing by the device and components of the device were considered. For the increasing information processing speed was used 32bit controller and graphic equalizer with seven passbands. Music visualization it is function, that are spread widely in mediaplayer’s software, on a different operation systems. This function shows animated images that are depends on music signal. Images are usually reproduced in the real time mode and synchronized with a played audio-track. Music and visualization are merges in the different kind of art: opera, ballett, music drama or movies. Dependencies of auditory and visual sensations are used for increasing the emotional perseption for ordinary listeners . In the systems, that are currently being actively promoted, are used several tools for personal computers, such as: After Effects – The Audio Spectrum Effect, VSDC Video Editor Free – Audio Spectrum Visualizer, Magic Music Visuals. The software, that are mentioned above, has a one disadvantage: the using of streaming video is not possible with the simultaneous receipt of audio and requires processing and rendering of the resulting video series. The purpose of the work is to determine the features of spectral analysis of music information and taking into account real-time data processing. Propose a variant of the music information visualization system, which displays the spectral composition of music and the amplitude of individual harmonics, and filling the LED-matrix with the appropriate color depending on the amplitude of the audio signal, with the possibility of wireless signal transmission from the music source to the visual effects device. The technology of frequency analysis of the spectrum with estimation of amplitude of spectrum’s components of the musical data, that is arriving on the device is chosen for this project. The method is based on the analysis of the spectrum in the selected frequency bands, which in turn simplifies the function of finding maxima at different frequencies. The proposed variant of the musical information visualization system provides display on the LED-matrix of colors that correspond to the frequencies spectrum’s components in the musical composition. Moreover, the number of involved LEDs is proportional to the ratio of the amplitudes of the signal’s frequency components. The desired result is achieved by using a Fast Fourier Transform and selecting Khan or Heming windows for providing a better analysis results of the signal spectrum. The amplitudes of the individual components of the spectrum are estimated additionally and each frequency band has its own color. The work of the system is to analyze the components of the spectrum and frequency of musical information. This information affects the display of colors on the LED matrix. The using of a 32-bit microcontroller provides sufficient speed of audio signal processing with minimal delays. For the increasing the accuracy and speed up the frequency analysis, the sound range is divided into seven bands. For this purpose was used seven-band graphic equalizer MSGEQ7. Music information is transmitted to the system via Bluetooth, which greatly simplifies the selection and connection of the music data source.

scholarly journals UAV real-time data acquisition and display visualization system based on three-dimensional route planning

2018 ◽  
Vol 1 (1) ◽  
pp. 39-43
Author(s):  
Lihong Chen ◽  
Yuxuan Li ◽  
Qionghai Huang ◽  
Haochen Hu ◽  
Jieting Chen ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Three Dimensional ◽  
Route Planning ◽  
Time Data ◽  
Visualization System ◽  
Real Time Data

Ambulatory Assessment

2009 ◽  
Vol 14 (2) ◽  
pp. 109-119 ◽  
Author(s):  
Ulrich W. Ebner-Priemer ◽  
Timothy J. Trull
Keyword(s):  
Real Time ◽  
Clinical Psychology ◽  
Real Life ◽  
Ambulatory Assessment ◽  
Computer Assisted ◽  
Affective Valence ◽  
Time Data ◽  
Physiological Processes ◽  
Context Specific ◽  
Questionnaire Studies

Convergent experimental data, autobiographical studies, and investigations on daily life have all demonstrated that gathering information retrospectively is a highly dubious methodology. Retrospection is subject to multiple systematic distortions (i.e., affective valence effect, mood congruent memory effect, duration neglect; peak end rule) as it is based on (often biased) storage and recollection of memories of the original experience or the behavior that are of interest. The method of choice to circumvent these biases is the use of electronic diaries to collect self-reported symptoms, behaviors, or physiological processes in real time. Different terms have been used for this kind of methodology: ambulatory assessment, ecological momentary assessment, experience sampling method, and real-time data capture. Even though the terms differ, they have in common the use of computer-assisted methodology to assess self-reported symptoms, behaviors, or physiological processes, while the participant undergoes normal daily activities. In this review we discuss the main features and advantages of ambulatory assessment regarding clinical psychology and psychiatry: (a) the use of realtime assessment to circumvent biased recollection, (b) assessment in real life to enhance generalizability, (c) repeated assessment to investigate within person processes, (d) multimodal assessment, including psychological, physiological and behavioral data, (e) the opportunity to assess and investigate context-specific relationships, and (f) the possibility of giving feedback in real time. Using prototypic examples from the literature of clinical psychology and psychiatry, we demonstrate that ambulatory assessment can answer specific research questions better than laboratory or questionnaire studies.

399-P: Nurse-Driven Intervention Using Real-Time Data to Improve Hypoglycemia Rates in a Respiratory Care Unit

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 399-P
Author(s):  
ANN MARIE HASSE ◽  
RIFKA SCHULMAN ◽  
TORI CALDER
Keyword(s):  
Real Time ◽  
Respiratory Care ◽  
Time Data ◽  
Real Time Data

DESIGN OF THE VIRTUAL DEVICE FOR THE SIGNAL SPECTRUM CALCULATION IN THE LABVIEW ENVIRONMENT

2019 ◽  
Author(s):  
Tossenko O.M.
Keyword(s):  
Virtual Instrument ◽  
Spectral Characteristics ◽  
Spectral Composition ◽  
Automated System ◽  
Signal Spectrum ◽  
Measuring Instruments ◽  
Specific Information ◽  
Measuring Device ◽  
Virtual Device ◽  
Graphical Tool

The development of measuring instruments requires a specialist to know the principles of operation of advanced measuring systems. This article describes guidelines for creating a virtual appliance in LabVIEW. LabVIEW (Laboratory Virtual Instrument Engineering Workbench) is a graphical application programming environment used as a standard tool for measuring, analyzing their data, further ma­ naging devices and objects under study. LabVIEW language is not like other programming languages. It does not create a program, but a virtual tool, designed not only for the simulation of certain processes, but also for the management of hardware and the study of real physical objects. The article deals with the task of designing application software for a specific information-measuring device, analyzes the capabilities of the LabVIEW environment for spectral analysis of various signals, outlines the basic principles and techniques of programming within the framework of the LabVIEW graphical environment during the basic stages of development. The procedure for creating a virtual device is described, which allows to evaluate the spectral composition of the signals, presents a graphical code of execution (diagram) to the program and a graphical tool interface of the virtual device. A number of basic elements used to develop the program are described. The simplicity of the graphic designs, the ease of installation on the field of the program, the clarity and readability of the program — all of which makes LabVIEW preferred over other languages of programming. In most cases, the experiment is the only source of reliable information. And the result is achieved much faster than the methods of "pure" theory. The article substantiates the effectiveness of using a development tool that allows to obtain a software product and ensure the fulfillment of all the basic functions of an automated system. Developing a software algorithm for calculating statistical parameters will help engineering students understand the order of determining spectral characteristics and their place in the structure of experimental research.

MHA releases largest real‐time data from MH help‐seekers

2021 ◽  
Vol 31 (6) ◽  
pp. 7-7
Author(s):  
Valerie A. Canady
Keyword(s):  
Real Time ◽  
Time Data ◽  
Real Time Data

Why Ecological Momentary Assessment Surveys Go Incomplete?: When It Happens and How It Impacts Data

2020 ◽  
Author(s):  
Yu-Hsiang Wu ◽  
Jingjing Xu ◽  
Elizabeth Stangl ◽  
Shareka Pentony ◽  
Dhruv Vyas ◽  
...  
Keyword(s):  
Real Time ◽  
Self Report ◽  
Data Logging ◽  
Time Data ◽  
Real Time Data ◽  
Report Data ◽  
Self Report Data ◽  
Ecological Momentary ◽  
The Impact ◽  
Momentary Assessment

Abstract Background Ecological momentary assessment (EMA) often requires respondents to complete surveys in the moment to report real-time experiences. Because EMA may seem disruptive or intrusive, respondents may not complete surveys as directed in certain circumstances. Purpose This article aims to determine the effect of environmental characteristics on the likelihood of instances where respondents do not complete EMA surveys (referred to as survey incompletion), and to estimate the impact of survey incompletion on EMA self-report data. Research Design An observational study. Study Sample Ten adults hearing aid (HA) users. Data Collection and Analysis Experienced, bilateral HA users were recruited and fit with study HAs. The study HAs were equipped with real-time data loggers, an algorithm that logged the data generated by HAs (e.g., overall sound level, environment classification, and feature status including microphone mode and amount of gain reduction). The study HAs were also connected via Bluetooth to a smartphone app, which collected the real-time data logging data as well as presented the participants with EMA surveys about their listening environments and experiences. The participants were sent out to wear the HAs and complete surveys for 1 week. Real-time data logging was triggered when participants completed surveys and when participants ignored or snoozed surveys. Data logging data were used to estimate the effect of environmental characteristics on the likelihood of survey incompletion, and to predict participants' responses to survey questions in the instances of survey incompletion. Results Across the 10 participants, 715 surveys were completed and survey incompletion occurred 228 times. Mixed effects logistic regression models indicated that survey incompletion was more likely to happen in the environments that were less quiet and contained more speech, noise, and machine sounds, and in the environments wherein directional microphones and noise reduction algorithms were enabled. The results of survey response prediction further indicated that the participants could have reported more challenging environments and more listening difficulty in the instances of survey incompletion. However, the difference in the distribution of survey responses between the observed responses and the combined observed and predicted responses was small. Conclusion The present study indicates that EMA survey incompletion occurs systematically. Although survey incompletion could bias EMA self-report data, the impact is likely to be small.

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