Optimizing information‐transfer rates for human communication

2006 ◽  
Vol 119 (5) ◽  
pp. 3237-3237
Author(s):  
Charlotte M. Reed ◽  
Nathaniel I. Durlach ◽  
Hong Z. Tan
Keyword(s):  
Information Transfer ◽  
Human Communication ◽  
Transfer Rates

Note on Information Transfer Rates in Human Communication

1998 ◽  
Vol 7 (5) ◽  
pp. 509-518 ◽  
Author(s):  
Charlotte M. Reed ◽  
Nathaniel I. Durlach
Keyword(s):  
Sign Language ◽  
Information Transfer ◽  
Single Letter ◽  
Motor Output ◽  
Published Data ◽  
Close Correspondence ◽  
Human Communication ◽  
Transfer Rates ◽  
Language Communication ◽  
Normalized Units

Information-transfer (IT) rates in bits/sec were estimated for a variety of methods of human communication and modalities of reception. Using previously published data, a range of communication rates for which transmission is highly accurate was established for each method and modality. These communication rates were converted into a normalized unit of transmission (words/sec). The normalized units were then converted into estimates of IT rate (bits/sec) using Shannon's (1951) calculations of the information content of a single letter of the alphabet. Maximal estimates of IT rates of roughly 40 to 60 bits/sec are observed for speech (through audition) and for reading and sign language (through vision). Maximal rates roughly 50 percent lower are obtained for reading through the tactual sense. Estimates of IT rates for motor output tasks are also considered. A close correspondence is generally observed between IT rates for receiving a given display and IT rates for the motor output task required for producing the display. These results have implications for the design of synthetic-environment systems and the displays and controls to be used in these systems, by providing examples of communication rates that have been achieved by humans in the area of language communication.

scholarly journals A Hybrid Speller Design Using Eye Tracking and SSVEP Brain–Computer Interface

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 891 ◽  
Author(s):  
Malik M. Naeem Mannan ◽  
M. Ahmad Kamran ◽  
Shinil Kang ◽  
Hak Soo Choi ◽  
Myung Yung Jeong
Keyword(s):  
Eye Tracking ◽  
Classification Accuracy ◽  
Information Transfer ◽  
High Speed ◽  
Communication Channel ◽  
Computer Interface ◽  
Stimuli Responsive ◽  
Transfer Rates ◽  
Computer Interfaces ◽  
Large Numbers

Steady-state visual evoked potentials (SSVEPs) have been extensively utilized to develop brain–computer interfaces (BCIs) due to the advantages of robustness, large number of commands, high classification accuracies, and information transfer rates (ITRs). However, the use of several simultaneous flickering stimuli often causes high levels of user discomfort, tiredness, annoyingness, and fatigue. Here we propose to design a stimuli-responsive hybrid speller by using electroencephalography (EEG) and video-based eye-tracking to increase user comfortability levels when presented with large numbers of simultaneously flickering stimuli. Interestingly, a canonical correlation analysis (CCA)-based framework was useful to identify target frequency with a 1 s duration of flickering signal. Our proposed BCI-speller uses only six frequencies to classify forty-eight targets, thus achieve greatly increased ITR, whereas basic SSVEP BCI-spellers use an equal number of frequencies to the number of targets. Using this speller, we obtained an average classification accuracy of 90.35 ± 3.597% with an average ITR of 184.06 ± 12.761 bits per minute in a cued-spelling task and an ITR of 190.73 ± 17.849 bits per minute in a free-spelling task. Consequently, our proposed speller is superior to the other spellers in terms of targets classified, classification accuracy, and ITR, while producing less fatigue, annoyingness, tiredness and discomfort. Together, our proposed hybrid eye tracking and SSVEP BCI-based system will ultimately enable a truly high-speed communication channel.

scholarly journals Brain–Computer Interface Spellers for Communication: Why We Need to Address Their Security and Authenticity

2020 ◽  
Vol 10 (3) ◽  
pp. 139
Author(s):  
Anirban Dutta
Keyword(s):  
Research And Development ◽  
Information Transfer ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Brain Computer Interfaces ◽  
Transfer Rates ◽  
Computer Interfaces ◽  
Significant Research

Brain–Computer Interfaces (BCI) have witnessed significant research and development in the last 20 years where the main aim was to improve their accuracy and increase their information transfer rates (ITRs), while still making them portable and easy to use by a broad range of users [...]

scholarly journals INFORMATION TRANSFER RATES IN SPIN QUANTUM CHANNELS

2007 ◽  
Vol 05 (04) ◽  
pp. 439-455 ◽  
Author(s):  
DAVIDE ROSSINI ◽  
VITTORIO GIOVANNETTI ◽  
ROSARIO FAZIO
Keyword(s):  
Quantum Information ◽  
Information Transfer ◽  
Transmission Efficiency ◽  
Spin Chains ◽  
Quantum Channels ◽  
Transfer Rates ◽  
Temporal Correlations ◽  
Spin Quantum ◽  
Communication Efficiency

We analyze the communication efficiency of quantum information transfer along unmodulated spin chains by computing the communication rates of various protocols. The effects of temporal correlations are discussed, showing that they can be exploited to boost the transmission efficiency.

scholarly journals High-speed spelling with a noninvasive brain–computer interface

2015 ◽  
Vol 112 (44) ◽  
pp. E6058-E6067 ◽  
Author(s):  
Xiaogang Chen ◽  
Yijun Wang ◽  
Masaki Nakanishi ◽  
Xiaorong Gao ◽  
Tzyy-Ping Jung ◽  
...  
Keyword(s):  
Information Transfer ◽  
High Speed ◽  
Target Identification ◽  
Modulation Method ◽  
Identification Algorithm ◽  
Calibration Data ◽  
Transfer Rates ◽  
Modulation And Demodulation ◽  
Individual Calibration ◽  
High Consistency

The past 20 years have witnessed unprecedented progress in brain–computer interfaces (BCIs). However, low communication rates remain key obstacles to BCI-based communication in humans. This study presents an electroencephalogram-based BCI speller that can achieve information transfer rates (ITRs) up to 5.32 bits per second, the highest ITRs reported in BCI spellers using either noninvasive or invasive methods. Based on extremely high consistency of frequency and phase observed between visual flickering signals and the elicited single-trial steady-state visual evoked potentials, this study developed a synchronous modulation and demodulation paradigm to implement the speller. Specifically, this study proposed a new joint frequency-phase modulation method to tag 40 characters with 0.5-s-long flickering signals and developed a user-specific target identification algorithm using individual calibration data. The speller achieved high ITRs in online spelling tasks. This study demonstrates that BCIs can provide a truly naturalistic high-speed communication channel using noninvasively recorded brain activities.

scholarly journals INFORMATION TRANSFER TECHNIQUE IN TEACHING WRITING

2014 ◽  
Vol 3 (1) ◽  
pp. 97
Author(s):  
Ummi Khaerati Syam ◽  
Ismail Sangkala
Keyword(s):  
Information Transfer ◽  
Sampling Technique ◽  
Teaching Writing ◽  
Human Communication ◽  
Writing Ability ◽  
First Semester ◽  
Writing Test ◽  
Good Writing ◽  
Good Technique ◽  
The One

Writing is one of the language skills that plays important role in human communication. It is used to communicate with other people in society and also to express our opinion in writing form. The teaching of writing requires the students to write accurately. Have a good competence in English does not only mean to be fluent speakers of the language, as many people have in mind but in writing as well; a lot of varieties of occupations require skilled people in English both in speaking and writing. There are some factors that influence the students’ ability to write; they are the vocabulary, the interesting topics were given the interest of students in learning writing such as picture, map, graphic, etc and the time to teach writing in English course or inappropriate technique. Among these factors, technique is an important factor that should be given a special attention because by applying a good technique, the students can improve their ability to organize their ideas into a good writing. This research is intended to find out the improvement of the students’ writing ability by using Information Transfer Technique at first semester students’ of Muhammadiyah University of Makassar. The method will use a Pre-Experimental research with the one group pretest and posttest design. The sample is only one class that consisted of 40 students which were selected by using Purposive sampling technique. The data were obtained through writing test.

Information Transfer Through Stochastic Transmission of a Linear Combination of Rates

2013 ◽  
Vol 25 (9) ◽  
pp. 2265-2302 ◽  
Author(s):  
Ioannis Smyrnakis ◽  
Stelios Smirnakis
Keyword(s):  
Linear Combination ◽  
Information Transfer ◽  
Firing Process ◽  
Afferent Neurons ◽  
Rate Code ◽  
Transfer Rates ◽  
Firing Rates ◽  
Information Transfer Rate ◽  
The Individual ◽  
High Firing

In this work, the Shannon information transfer rate due to the transmission of a linear combination of the firing rates of a number of afferent neurons is examined. The transmission of this linear combination (transfer statistic) takes place through a stochastic firing process, while a rate code is assumed. Constraints are imposed on the transmission process by the requirement that the coefficient of variation for the transfer statistic is small and by the relative variance of the individual terms in the calculation of the statistic. In the regime of no noise or signal correlations among the input neurons, simulations suggest that information transfer for fixed overall input is favored when there are few high-firing neurons, as opposed to more lower-firing neurons. Signal correlations among low-firing neurons can result in aggregates of high firing rates, improving in this way information transfer and calculational robustness. Under reasonable rate code assumptions, information transfer rates obtained are of the order 3 to 10 bit/sec.

scholarly journals How many bits of information can be transferred between residues in a protein and how fast?

2022 ◽  
Author(s):  
Aysima Hacisuleyman ◽  
Burak Erman
Keyword(s):  
Information Transfer ◽  
Activity Time ◽  
Perfect Agreement ◽  
Time Resolved ◽  
Transfer Rates ◽  
Entropy Transfer ◽  
Raman And Infrared Spectroscopy ◽  
Ultraviolet Resonance Raman ◽  
Basic Features ◽  
Gaussian Network

Time resolved Raman and infrared spectroscopy experiments show the basic features of information transfer between residues in proteins. Here, we present the theoretical basis of information transfer using a simple elastic net model and recently developed entropy transfer concept in proteins. Mutual information between two residues is a measure of communication in proteins which shows the maximum amount of information that may be transferred between two residues. However, it does not explain the actual amount of transfer nor the transfer rate of information between residues. For this, dynamic equations of the system are needed. We used the Schreiber theory of information transfer and the Gaussian network Model of proteins, together with the solution of the Langevin equation, to quantify allosteric information transfer. Results of the model are in perfect agreement with ultraviolet resonance Raman measurements. Analysis of the allosteric protein Human NAD-dependent isocitrate dehydrogenase shows that a multitude of paths contribute collectively to information transfer. While the peak values of information transferred are small relative to information content of residues, considering the estimated transfer rates, which are in the order of megabits per second, sustained transfer during the activity time-span of proteins may be significant.

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