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In this paper designing of a battery operated portable single channel electroencephalography (EEG) signal acquisition system is presented. The advancement in the field of hardware and signal processing tools made possible the utilization of brain waves for the communication between humans and computers. The work presented in this paper can be said as a part of bigger task, whose purpose is to classify EEG signals belonging to a varied set of mental activities in a real time Brain Computer Interface (BCI). Keeping in mind the end goal is to research the possibility of utilizing diverse mental tasks as a wide correspondence channel in the middle of individuals and PCs. This work deals with EEG based BCI, intent on the designing of portable EEG signal acquisition system. The EEG signal acquisition system with a cut off frequency band of 1-100 Hz is designed by the use of integrated circuits such as low power instrumentation amplifier INA128P, high gain operational amplifiers LM358P. Initially the amplified EEG signals are digitized and transmitted to a PC by a data acquisition module NI DAQ (SCXI-1302). These transmitted signals are then viewed and stored in the LAB VIEW environment. From a varied set of experimental observation it can be said that the system can be implemented in the acquisition of EEG signals and can stores the data to a PC efficiently and the system would be of advantage to the use of EEG signal acquisition or even BCI application by adapting signal processing tools.
Seattle Interactive Conference presentation by Vectorform's Director of Product Vision, Kevin Foreman.
While smart home technologies have existed for over 20 years, they continue to struggle with gaining a foothold within the average home, as many homeowners are skeptical to the benefits and advantages of the connected home lifestyle. Kevin will provide an insightful look at the journey from concept to delivery that re-invents the smart home experience.
#SIC2014
Contact us for more information and how we can help you on your next project sales@vectorform.com
In this paper designing of a battery operated portable single channel electroencephalography (EEG) signal acquisition system is presented. The advancement in the field of hardware and signal processing tools made possible the utilization of brain waves for the communication between humans and computers. The work presented in this paper can be said as a part of bigger task, whose purpose is to classify EEG signals belonging to a varied set of mental activities in a real time Brain Computer Interface (BCI). Keeping in mind the end goal is to research the possibility of utilizing diverse mental tasks as a wide correspondence channel in the middle of individuals and PCs. This work deals with EEG based BCI, intent on the designing of portable EEG signal acquisition system. The EEG signal acquisition system with a cut off frequency band of 1-100 Hz is designed by the use of integrated circuits such as low power instrumentation amplifier INA128P, high gain operational amplifiers LM358P. Initially the amplified EEG signals are digitized and transmitted to a PC by a data acquisition module NI DAQ (SCXI-1302). These transmitted signals are then viewed and stored in the LAB VIEW environment. From a varied set of experimental observation it can be said that the system can be implemented in the acquisition of EEG signals and can stores the data to a PC efficiently and the system would be of advantage to the use of EEG signal acquisition or even BCI application by adapting signal processing tools.
Seattle Interactive Conference presentation by Vectorform's Director of Product Vision, Kevin Foreman.
While smart home technologies have existed for over 20 years, they continue to struggle with gaining a foothold within the average home, as many homeowners are skeptical to the benefits and advantages of the connected home lifestyle. Kevin will provide an insightful look at the journey from concept to delivery that re-invents the smart home experience.
#SIC2014
Contact us for more information and how we can help you on your next project sales@vectorform.com
Glasses for the blind using ping ultrasonic, ATMEGA8535 and ISD25120TELKOMNIKA JOURNAL
For doing their activities, blind people need tools. The idea for designing this device is for helping the blind person. This device is a glasses specially for blind person which gives information in the form of voices through an earphone if there is an obstacle in the range of 0–58 cm. The device is using PING ultrasonic sensor, ATMEGA8535 microcontroller, and ISD25120 for recording and saving the voices. After designing and making the device, we tested the device to take the data. We use three PING ultrasonic sensors which are put at the sides of the glasses. The device will give eight different kinds of voices through the earphone. The voices depend upon the output of the PING ultrasonic sensors.
This final year project is basically about a robot controlled by a headband sensor called Neurosky Mind Wave. The robot is connected to the Arduino by Bluetooth.
The interface combines Speech and Tongue Motion for People with Severe Disabilities. This can help people with severe disabilities to become more independent.
A brain-computer interface sometimes called a direct neural interface or a brain-machine interface is a direct communication pathway between a human or animal brain(or brain cell culture) and an external device. In one BCIs, computers either accept commands from the brain or send signals to it but not both. Two-way BCIs will allow brains and external devices to exchange information in both directions but have yet to be successfully implanted in animals or humans.
2. Partially Invasive BCI: Partially invasive BCI devices are implanted inside the skull but rest outside the brain rather than amidst the grey matter. They produce better resolution signals than non-invasive BCIs where the bone tissue of the cranium deflects and deforms signals and have a lower risk of forming scar tissue in the brain than fully-invasive BCIs.
3. Non-Invasive BCI: Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) have both been used successfully as non-invasive BCIs.
There are three types of BCI
1. Inversive BCI: - Invasive BCI is directly implanted into the grey matter of the brain during neurosurgery. They produce the highest quality signals of BCI devices. Invasive BCIs has targeted repairing damaged sight and providing new functionality to paralysed people.
Design of an IOT based Online Monitoring Digital StethoscopeIJAAS Team
Acoustic stethoscopes have low sound levels. Digital stethoscope overcomes this issue by amplifying body sounds electronically. As the sound signals are transmitted electronically, it can be wireless and can provide noise reduction. Acoustic stethoscope can be changed into a digital stethoscope by inserting an electric capacity microphone onto its head. Heart sounds received from the microphone are processed, sampled and sound signals are converted analog to digital and sent wirelessly using the Internet of Things(IOT) techniques, so that multiple doctors can do auscultation and monitor conditions of the patient.
Glasses for the blind using ping ultrasonic, ATMEGA8535 and ISD25120TELKOMNIKA JOURNAL
For doing their activities, blind people need tools. The idea for designing this device is for helping the blind person. This device is a glasses specially for blind person which gives information in the form of voices through an earphone if there is an obstacle in the range of 0–58 cm. The device is using PING ultrasonic sensor, ATMEGA8535 microcontroller, and ISD25120 for recording and saving the voices. After designing and making the device, we tested the device to take the data. We use three PING ultrasonic sensors which are put at the sides of the glasses. The device will give eight different kinds of voices through the earphone. The voices depend upon the output of the PING ultrasonic sensors.
This final year project is basically about a robot controlled by a headband sensor called Neurosky Mind Wave. The robot is connected to the Arduino by Bluetooth.
The interface combines Speech and Tongue Motion for People with Severe Disabilities. This can help people with severe disabilities to become more independent.
A brain-computer interface sometimes called a direct neural interface or a brain-machine interface is a direct communication pathway between a human or animal brain(or brain cell culture) and an external device. In one BCIs, computers either accept commands from the brain or send signals to it but not both. Two-way BCIs will allow brains and external devices to exchange information in both directions but have yet to be successfully implanted in animals or humans.
2. Partially Invasive BCI: Partially invasive BCI devices are implanted inside the skull but rest outside the brain rather than amidst the grey matter. They produce better resolution signals than non-invasive BCIs where the bone tissue of the cranium deflects and deforms signals and have a lower risk of forming scar tissue in the brain than fully-invasive BCIs.
3. Non-Invasive BCI: Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) have both been used successfully as non-invasive BCIs.
There are three types of BCI
1. Inversive BCI: - Invasive BCI is directly implanted into the grey matter of the brain during neurosurgery. They produce the highest quality signals of BCI devices. Invasive BCIs has targeted repairing damaged sight and providing new functionality to paralysed people.
Design of an IOT based Online Monitoring Digital StethoscopeIJAAS Team
Acoustic stethoscopes have low sound levels. Digital stethoscope overcomes this issue by amplifying body sounds electronically. As the sound signals are transmitted electronically, it can be wireless and can provide noise reduction. Acoustic stethoscope can be changed into a digital stethoscope by inserting an electric capacity microphone onto its head. Heart sounds received from the microphone are processed, sampled and sound signals are converted analog to digital and sent wirelessly using the Internet of Things(IOT) techniques, so that multiple doctors can do auscultation and monitor conditions of the patient.
Microcontroller Based Obstacle Detection Device Using Voice Signal for the V...IJMER
This paper aims in helping the visually impaired people through an electronic aid, which
senses any obstacle in the path and alarms the user of the obstacle. The device uses a simple principle of
transmitting an ultrasonic signal in the path generated by a wave generator. The signal gets reflected by
the obstacle (if any) in the path. The reflected signal is sensed by a sensor and produces a sound signal in
the form of voice. This voice signal directs the visually impaired person to identify the obstacles in front
of them
Handicapped Assistance Device for Controlling Electrical Appliances Jamuna R - Assistant Professor,
Abhinai S - UG scholar,
Jhananadhan SP - UG scholar,
Department of ECE,
SNS College of Engineering, Coimbatore, India
A Smart Handheld Measuring and Testing Electronic Device with Touch ScreenIJTET Journal
Hand in hand instrument replaces the old traditional way of measuring and testing in colleges and helps in easy way of understanding theoretical concepts based on practical knowledge. As there occurs shortage of instruments, long duration of calculation, large occupation of space, low accuracy, inconvenience come about in completing the work. A single Smart device which is a multipurpose handheld instrument overcomes the above difficulties and helps in measuring voltage, current, resistance, frequency, temperature, speed, sound and to observe waveforms for engineering students in the laboratories. In a single ARM Cortex M3 microcontroller all measurements are done and displayed within a fraction of time in the TFT graphical LCD display. The data and waveforms from oscilloscope can be saved and retrieved for future analyzing purpose which is done using a Micro SD memory card. The device is fully operated with touch screen and touch buttons. The device works with help of LPC1313, a powerful 32-bit ARM Cortex-M3 microcontroller from NXP Semiconductors.
Application of Digital Signal Processing In Echo Cancellation: A SurveyEditor IJCATR
The advanced communications world is worried talking more naturally by using hands free this help the human being to talk
more confidently without holding any of the devices such as microphones or telephones. Acoustic echo cancellation and noise
cancellers are quite interesting nowadays because they are required in many applications such as speakerphones and audio/video
conferencing. This paper describes an alternative method of estimating signals corrupted by additive noise or interference. Acoustic
echo cancellation problem was discussed out of different noise cancellation techniques by concerning different parameters with their
comparative results .The results shown are using some specific algorithm
This slide tells about how we operate the electrical instruments using the sound energy, as example given as a notice board operated using the clap sound.
International Journal of Computational Engineering Research(IJCER)
1. I nternational Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 8
Exploring a Microcontroller Based Hearing Aid with an Output Level
Indicator
1
Aru Okereke Eze , Eng. Dr. Gozie Ihekweaba and 3Ngwu Rosemary Chinyere
Depart ment of Co mputer Engineering
Michael Okpara Un iversity of Agriculture, Umudike, Umuahia, Abia State, Nigeria
Abstract:
This research explores the design and imp lementation of a microcontroller based electronic Hearing aid with output
level indicator. The incoming sound oscillates the base of a transistor which in turn amplifies the signal at the collect or. The
output is interfaced to an ADC wh ich converts the signal to digital output. After the conversion, the microcontroller
processes the signal and further feeds it in to the DAC for an analog conversion. This output is now fed into the audio level
indicator, LM 3915, to indicate the level of the audio signal at the ear phone.
Keywords: Microcontroller, Hearing Aid, Digital, Ear, Noise, Electronics.
1. Introduction
Dig ital hearing aids can do wonders for faded hearing. With the technological advancement in the society, hearing
aids can significantly enhance the quality of life for most people with hearing impairment. Therefore, the electronic hearing
aid is designed to make sounds louder and therefore easier to hear. Also the design of the circuitry keeps the sound from
becoming too loud and helps reduce the effects of background noise.
The two basic types of technology for hearing aids are analog and digital. The first to exist, analog hearing aids
process electrical sound in the analog domain; the more recent digital hearing aids process electrical sound in the digital
domain. The earliest analog hearing aids simply amp lified both speech and noise, and were ordered after testing to
determine the particular frequency response needed by the patient. Newer a nalog hearing aids can be programmed during
the fitting process, and some have multiple listening profiles that the patient can select with a button on the hearing aid.[ 1].
Manufacturers are moving toward their third or fourth generation of digital products. Digital technology is more stable over
time. There are fewer co mponents to go wrong and fewer co mponents that are susceptible to moisture and aging changes.
This means that the sound you experience on the first day you receive the hearing aid stays cons istent until the program is
changed.[2] In recent years, there has been an increasing trend toward fitting BTE( Behind The Ear) hearing aids,
including receiver-in-canal (RIC) instru ments. It is estimated that 51% of the hearing aids fitted in the U.S. are BTE
instruments, rather than custom products [3]. In a survey by Kochkin of 2500 hearing aid users, patients reported a desire for
hearing aids that do not feedback (85%), fit comfo rtably (79%), and are less visible (52%) [4]. In this work, we will explore
a digital hearing aid with Output level indicator (LM 3915) using the microcontroller Atmel 89c52, analog and digital
converters.
We preset in section 2 system design, section 3 principle of operation, section 4 user guide, section 5 Conclusion.
2. System Design
The system is designed in such a way that the output is an analog signal which needs to be converted into digital
signal for onward interface to a microcontroller. In th is work, the ADC was handy to settle the conversion problem. It
converts the analog signal to digital signal. After the conversion processes, the microcontroller gives out a digital output
which requires conversion back to its analog state. Hence, the output signal can be connected to a microphone to ascertain
the nature of the signal.
This analog output is then fed into lm3915, an audio level indicator, to process and give a required graphic result of
the signal strength. Apart from analog and digital conversions, the emphasis is also on the individual components of the
devices employed and their relevance to the design.
Some of the materials used in this work are listed below:
Audio level indicator (LM 3915)
Analog-to-digital converter (ADC0804)
Dig ital-to-analog converter (DA C0808)
Microcontroller (At mel 89c52)
Resistors
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2. I nternational Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 8
Capacitors
Transistors
Light Emitt ing Diodes (LED)
Ear Phones
Figure 1: Block Di agram of Hearing Ai d
Microphone Broadband Circuit to be
Amplifier Designed:
Custom Filtering
Circuit to Undo
Hearing Losses
Audio
Earphone
Amplifier
Figure 2. Functional Diagram of Hearing Aid.
FIG 3. CIRCUIT DIA GRAM OF THE DESIGN
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3. I nternational Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 8
3. Principle Of Operation
The electret mic used in this project is positioned in such a way as to pick noise which is very suitable for hearing
aid. The power supply should be 9V so as to pick small signal. The incoming sound oscillates the base of a transistor which
in turn amp lifies the signal at the collector. The output is interfaced to an ADC which converts the signal to digital output.
This is necessary because the microcontroller cannot understand analog signal and therefore cannot process it. After the
conversion, the microcontroller processes the signal and further feeds it in to the DAC for an analog conversion.
By so doing, the original signal is replicated at the other end, though in its amplified form. This output is now fed
into the audio level indicator, LM 3915, to indicate the level of the audio signal at the ear phone. However, this level can be
controlled or adjusted according to one’s desire, using a potentiometer. One end of the earphone is plugged into the jack on
the system and the other end in the ear.
The subsystems of this work were interconnected or integrated to work as a system. The integration of this system
is necessary so as to tailor each unit of the system to perform a targeted result. The transducer was interconnected to analo g-
to- digital converter to be able convert the analog quantity of the ambient temperature to a digital output. The ADC in turn
was interfaced to a microcontroller for processing and giving its digital output to a DAC to reconvert to an analog signal.
With all these interconnectivity, the different subsystems can now be said to be working as a system, in that they can
interact with each other to produce a definite result.
US ER GUID E
To use the microcontroller based hearing aid, Power ON the switch and the red LED co mes on. Plug in the Ear
phones and Listen. The audio level is indicated by the five LEDs on the box. The loudest level is indicated by the yellow
LED. Power OFF when not in use to avoid running the battery down. If the audio level LEDs glow continuously or do not
correspond to the level of sound, then turn OFF the switch and ON again. If it persists, it could be as a result of either low
battery or microcontroller lock up.
4. Conclusion
No matter what you do for a living, impaired hearing will affect your job performance. This is the information age
and one of the primary ways to receive information is through hearing. The microcontroller based digital hearing aid can go
a long way to achieve in people, increased enjoyment of social activities, improved ability to use the telephone, greater
enjoyment of television and music, improved relationships and understanding of speech, increased ability to hear
environmental sounds, increased self esteem and greater confidence. The design of the hardware using available
components was achieved based on the principles of operation of individual electronic devices. The software program
entails writing of p rograms that will drive the other subsystems to perform the desired operation.
References
[1]. Rickets T.A. (2011) Dig ital Hearing Aids: “Current state of the art” retrieved September 04, 2012 fro m
http://www.asha.org/public/hearing/treatment/digital_aid.ht m
[2]. Imran khan(2012) Advanced Hearing Aid Technology Retrieved September 20 2012, fro m
http://www.eldercareresourcespittsburgh.com/advanced-hearing-aid-technology/
[3]. Alexandria V (2006) Hearing Industries Association.(HIA) special survey results on BTEs, directional and telecoil
use. HIA journal 11, 15-25
Aru, Okereke Eze is a lecturer in the Department of Co mputer Engineering, Michael Okpara University of Agriculture,
Umuahia, Abia State, Nigeria. His research
Interests include Computer Hard ware design and maintenance, digital systems design using microcontrollers and other
computer related subjects.
Ng wu, Chinyere Rosemary is a student in the Department of Co mputer Engineering, M ichael Okpara Un iversity of
Agriculture, Umuahia, Abia State, Nigeria. Her research interests include Co mputer Hardware design and maintenance,
digital systems design using microcontrollers, etc.
Eng. Dr. Gozie Ihek weaba is a senior lecturer in the Department of Co mputer Engineering, Michael Okpara University of
Agriculture, Umuahia, Abia State, Nigeria. His research Interests include Computer Hard ware design and maintenance,
digital systems design, Digital Electronics and other computer related subjects
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