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Articoli di riviste sul tema "Deaf and Dumb Institution"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 15 febbraio 2022

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1

Gupta, Amit. "Blind, Deaf and Dumb Communicator". International Journal for Research in Applied Science and Engineering Technology 6, n. 6 (30 giugno 2018): 1648–52. http://dx.doi.org/10.22214/ijraset.2018.6242.

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Tomar, Niraj Singh. "Virtual Assistant for Deaf and Dumb". International Journal for Research in Applied Science and Engineering Technology 8, n. 4 (30 aprile 2020): 307–10. http://dx.doi.org/10.22214/ijraset.2020.4048.

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van Dongen, H. R., e M. C. B. Loonen. "Blind, deaf and dumb after Shigellosis". Clinical Neurology and Neurosurgery 93, n. 1 (gennaio 1991): 84. http://dx.doi.org/10.1016/0303-8467(91)90022-h.

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K J, Monika. "Conversation Engine for Deaf and Dumb". International Journal for Research in Applied Science and Engineering Technology 9, n. VII (25 luglio 2021): 2271–75. http://dx.doi.org/10.22214/ijraset.2021.36841.

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Deaf and hard hearing people use linguistic communication to exchange information between their own community and with others. Sign gesture acquisition and text/speech generation are parts of computer recognition of linguistic communication. Static and dynamic are classified as sign gestures. Both recognition systems are important to the human community but static gesture recognition is less complicated than dynamic gesture recognition. Inability to talk is taken into account to be a disability among people. To speak with others people with disability use different modes, there are number of methods available for his or her communication one such common method of communication is linguistic communication. Development of linguistic communication recognition application for deaf people is vital, as they’ll be able to communicate easily with even people who don’t understand language. Our project aims at taking the fundamental step in removing the communication gap between normal people, deaf and dumb people using language.

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Dabade, Akshata, Anish Apte, Aishwarya Kanetkar e Sayali Pisal. "Two Way Communication between Deaf & Dumb". International Journal of Computer Trends and Technology 40, n. 3 (25 ottobre 2016): 114–18. http://dx.doi.org/10.14445/22312803/ijctt-v40p122.

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Buvaneswari, B., T. Hemalatha, G. Kalaivani, P. Pavithra e A. R. Preethisree. "Communication among blind, deaf and dumb People". International Journal of Advanced Engineering, Management and Science 6, n. 4 (2020): 173–76. http://dx.doi.org/10.22161/ijaems.64.2.

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Shah, Disha. "Sign Language Recognition for Deaf and Dumb". International Journal for Research in Applied Science and Engineering Technology 9, n. 5 (31 maggio 2021): 2087–92. http://dx.doi.org/10.22214/ijraset.2021.34770.

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Kour, Kamal Preet, e Lini Mathew. "Sign Language Recognition Using Image Processing". International Journal of Advanced Research in Computer Science and Software Engineering 7, n. 8 (30 agosto 2017): 142. http://dx.doi.org/10.23956/ijarcsse.v7i8.41.

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One of the major drawback of our society is the barrier that is created between disabled or handicapped persons and the normal person. Communication is the only medium by which we can share our thoughts or convey the message but for a person with disability (deaf and dumb) faces difficulty in communication with normal person. For many deaf and dumb people , sign language is the basic means of communication. Sign language recognition (SLR) aims to interpret sign languages automatically by a computer in order to help the deaf communicate with hearing society conveniently. Our aim is to design a system to help the person who trained the hearing impaired to communicate with the rest of the world using sign language or hand gesture recognition techniques. In this system, feature detection and feature extraction of hand gesture is done with the help of SURF algorithm using image processing. All this work is done using MATLAB software. With the help of this algorithm, a person can easily trained a deaf and dumb.

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Patil, Shweta S. "Sign Language Interpreter for Deaf and Dumb People". International Journal for Research in Applied Science and Engineering Technology 7, n. 9 (30 settembre 2019): 354–59. http://dx.doi.org/10.22214/ijraset.2019.9050.

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Sharma, Deepak, Kenil Vora e Shivam Shukla. "HAND ASSISTIVE DEVICE FOR DEAF AND DUMB PEOPLE." International Journal of Advanced Research 5, n. 10 (31 ottobre 2017): 1042–46. http://dx.doi.org/10.21474/ijar01/5623.

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Manandhar, Sanish, Sushana Bajracharya, Sanjeev Karki e Ashish Kumar Jha. "Hand Gesture Vocalizer for Dumb and Deaf People". SCITECH Nepal 14, n. 1 (9 settembre 2019): 22–29. http://dx.doi.org/10.3126/scitech.v14i1.25530.

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The main purpose of this paper is to confer the system that converts a given sign used by disabled person into its appropriate textual, audio, and pictorial form using components such as Arduino Mega, Flex sensors, Accelerometer, which could be under standby a common person. A wearable glove controller is design with fl ex sensors attached on each finger, which allows the system to sense the finger movements, and aGy-61 accelerometer, which are uses to sense the hand movement of the disabled person. The wearable input glove controller sends the collected input signal to the system for processing. The system uses Random forest algorithm to predict the correct output to an accuracy of 85% on current training model.

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Callanan, Vincent, e Alec Fitzgerald O'Connor. "Making the deaf hear and the dumb speak". Lancet 348 (dicembre 1996): S19. http://dx.doi.org/10.1016/s0140-6736(96)98029-0.

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Alhassan, Fatemah, Mona Elharbi, Mai Elharbi e Amjad Alqanny. "Technology-based services for deaf and dumb people". International Journal of Data Science 5, n. 2 (2020): 160. http://dx.doi.org/10.1504/ijds.2020.10034183.

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Alhassan, Fatemah, Amjad Alqanny, Mai Elharbi e Mona Elharbi. "Technology-based services for deaf and dumb people". International Journal of Data Science 5, n. 2 (2020): 160. http://dx.doi.org/10.1504/ijds.2020.112136.

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., Gowri D. "SIGN LANGUAGE RECOGNITION FOR DEAF AND DUMB PEOPLE". International Journal of Research in Engineering and Technology 03, n. 19 (25 maggio 2014): 797–99. http://dx.doi.org/10.15623/ijret.2014.0319144.

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., Sudheesh Narayanan. "COMMUNICATION AID WITH HOME AUTOMATION FOR DEAF DUMB". International Journal of Research in Engineering and Technology 04, n. 15 (25 aprile 2015): 5–8. http://dx.doi.org/10.15623/ijret.2015.0415002.

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Harshada, Ajabe. "Smart Communication Assistant for Deaf and Dumb People". International Journal for Research in Applied Science and Engineering Technology 9, n. VII (15 luglio 2021): 1358–60. http://dx.doi.org/10.22214/ijraset.2021.36437.

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Communication is the medium by which we can share our thoughts or convey the messages with other person. Nowadays we can give commands using voice recognition. But what if one absolutely cannot hear anything and eventually cannot speak. So the Sign Language is the main communicating tool for hearing impaired and mute people, and also to ensure an independent life for them, the automatic interpretation of sign language is an extensive research area. Sign language recognition (SLR) aims to interpret sign languages automatically by an application in order to help the deaf people to communicate with hearing society conveniently. Our aim is to design a system to help the Deaf and Dumb person to communicate with the rest of the world using sign language. With the use of image processing and artificial intelligence, many techniques and algorithms have been developed in this area. Every sign language recognition system is trained for recognizing the signs and converting them into required pattern. The proposed system aim to provide speech to speechless, in this paper we have introduced Sign Language Recognition using CNN for dynamic gestures to achieve faster results with high accuracy.

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Dhake, Dipali, Manisha P. Kamble, Shrushti S. Kumbhar e Sana M. Patil. "SIGN LANGUAGE COMMUNICATION WITH DUMB AND DEAF PEOPLE". International Journal of Engineering Applied Sciences and Technology 5, n. 4 (1 agosto 2020): 254–58. http://dx.doi.org/10.33564/ijeast.2020.v05i04.038.

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Unruh, W. G. "Dumb holes: analogues for black holes". Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 366, n. 1877 (5 giugno 2008): 2905–13. http://dx.doi.org/10.1098/rsta.2008.0062.

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The use of sonic analogues to black and white holes, called dumb or deaf holes, to understand the particle production by black holes is reviewed. The results suggest that the black hole particle production is a low-frequency and low-wavenumber process.

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Ranganathan, T., P. Hephzibah, M. Jagadesh, R. Jegadees e S. Kanimozhi. "Hand Talk-An Assistive Technology for Deaf and Dumb". Indian Journal of Public Health Research & Development 10, n. 2 (2019): 1076. http://dx.doi.org/10.5958/0976-5506.2019.00440.6.

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Singh, Mr Sushant. "Wirefree Glove: Gesture Vocalizer for Deaf and Dumb People". International Journal for Research in Applied Science and Engineering Technology 7, n. 4 (30 aprile 2019): 1184–88. http://dx.doi.org/10.22214/ijraset.2019.4211.

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Shrawankar, Urmila, e Shruti Gedam. "Finger Spelling in Air System for Deaf and Dumb". International Journal of Technology Diffusion 9, n. 1 (gennaio 2018): 28–44. http://dx.doi.org/10.4018/ijtd.2018010103.

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Finger spelling in air helps user to operate a computer in order to make human interaction easier and faster than keyboard and touch screen. This article presents a real-time video based system which recognizes the English alphabets and words written in air using finger movements only. Optical Character Recognition (OCR) is used for recognition which is trained using more than 500 various shapes and styles of all alphabets. This system works with different light situations and adapts automatically to various changing conditions; and gives a natural way of communicating where no extra hardware is used other than system camera and a bright color tape. Also, this system does not restrict writing speed and color of tape. Overall, this system achieves an average accuracy rate of character recognition for all alphabets of 94.074%. It is concluded that this system is very useful for communication with deaf and dumb people.

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Stark, Sharon W. "Blind, Deaf, and Dumb: Why Elder Abuse Goes Unidentified". Nursing Clinics of North America 46, n. 4 (dicembre 2011): 431–36. http://dx.doi.org/10.1016/j.cnur.2011.08.007.

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Jeyasheeli, Dr P. Golda, e N. Indumathi. "Sentence Generation for Indian Sign Language Using NLP". Webology 18, Special Issue 01 (29 aprile 2021): 196–210. http://dx.doi.org/10.14704/web/v18si01/web18054.

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Nowadays the interaction among deaf and mute people and normal people is difficult, because normal people scuffle to understand the sense of the gestures. The deaf and dumb people find problem in sentence formation and grammatical correction. To alleviate the issues faced by these people, an automatic sign language sentence generation approach is propounded. In this project, Natural Language Processing (NLP) based methods are used. NLP is a powerful tool for translation in the human language and also responsible for the formation of meaningful sentences from sign language symbols which is also understood by the normal person. In this system, both conventional NLP methods and Deep learning NLP methods are used for sentence generation. The efficiency of both the methods are compared. The generated sentence is displayed in the android application as an output. This system aims to connect the gap in the interaction among the deaf and dumb people and the normal people.

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Chong, Teak-Wei, e Boon-Giin Lee. "American Sign Language Recognition Using Leap Motion Controller with Machine Learning Approach". Sensors 18, n. 10 (19 ottobre 2018): 3554. http://dx.doi.org/10.3390/s18103554.

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Sign language is intentionally designed to allow deaf and dumb communities to convey messages and to connect with society. Unfortunately, learning and practicing sign language is not common among society; hence, this study developed a sign language recognition prototype using the Leap Motion Controller (LMC). Many existing studies have proposed methods for incomplete sign language recognition, whereas this study aimed for full American Sign Language (ASL) recognition, which consists of 26 letters and 10 digits. Most of the ASL letters are static (no movement), but certain ASL letters are dynamic (they require certain movements). Thus, this study also aimed to extract features from finger and hand motions to differentiate between the static and dynamic gestures. The experimental results revealed that the sign language recognition rates for the 26 letters using a support vector machine (SVM) and a deep neural network (DNN) are 80.30% and 93.81%, respectively. Meanwhile, the recognition rates for a combination of 26 letters and 10 digits are slightly lower, approximately 72.79% for the SVM and 88.79% for the DNN. As a result, the sign language recognition system has great potential for reducing the gap between deaf and dumb communities and others. The proposed prototype could also serve as an interpreter for the deaf and dumb in everyday life in service sectors, such as at the bank or post office.

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Nofal, Reem M. "Initiating android phone technology using QR codes to make innovative functional clothes". International Journal of Clothing Science and Technology 32, n. 6 (26 aprile 2020): 935–51. http://dx.doi.org/10.1108/ijcst-12-2018-0153.

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PurposeAndroid mobile phones are usually used in everyday life. QR (quick response) codes are one of the smart and interesting technologies to convey information fast and accurately through smartphones. So printing QR codes on different textiles by inkjet method concerns specific people, such as with Autism, and Down syndrome, deaf and dumb children and also people having Alzheimer’s disease, who do not have the ability to communicate to others properly; these people cannot know, express or remember information about their selves. So printing QR codes in their clothes can help improve their lives.Design/methodology/approachIn this study, different factors affecting QR codes scanability on fabrics were examined to clarify optimum conditions of recognition and readability. This paper examines different factors as QR Code different resolutions, sizes and lighting conditions. Different weave structures were also used. A questionnaire was done in a deaf and dumb school, for clarifying how QR codes can improve communication to some extent with others, especially those who do not realize sign language. In this study, different factors affecting QR codes’ scanability on fabrics were examined to clarify the optimum conditions of recognition and readability. This paper examines different factors as QR Code different resolutions, sizes and lighting conditions. Different weave structures were also used. A questionnaire was done in deaf and dumb school, to clarifying how QR codes can improve communication to some extent with others who especially do not realize sign language.FindingsThe finding of this study can provide basic data for future researches on QR codes printing on textiles. The effect of weave structure on QR code reading is obvious, as code reading time consumed in the plain fabric is more than that required in a twill structure. This economical method can enhance wearer life, especially for some cases as deaf and dumb cases.Originality/valueThese creative functions will surprise users and motivate them to scan the Codes. Increasing utility of QR codes in the textile and clothing field, give sustainability to the wearer clothes and accessories.

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Sharma, Chahat. "The Silent Voice - Communication Interface for Deaf and Dumb People". International Journal for Research in Applied Science and Engineering Technology 8, n. 5 (31 maggio 2020): 1711–16. http://dx.doi.org/10.22214/ijraset.2020.5277.

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V, Sneha, Sushma Desai e Sahana M. "Hand gesture based dumb and deaf communication using smart gloves". International Journal Of Engineering And Computer Science 7, n. 04 (2 aprile 2018): 23806–7. http://dx.doi.org/10.18535/ijecs/v7i4.01.

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The main aim of this paper is to provide voice to voiceless people with the help of Smart Gloves. With the proposed work, sign language is converted into speech using accelerometer and microcontrollers. where it reduces the communication barrier between two communities using the smart gloves

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Karmel, A., Anushka Sharma, Muktak pandya e Diksha Garg. "IoT based Assistive Device for Deaf, Dumb and Blind People". Procedia Computer Science 165 (2019): 259–69. http://dx.doi.org/10.1016/j.procs.2020.01.080.

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Ramaiah, Narayana Swamy, e Gawas Santoshi Shyamsundar. "An Electronic Glove-A Boon to the Deaf and Dumb". Journal of Physics: Conference Series 1172 (marzo 2019): 012018. http://dx.doi.org/10.1088/1742-6596/1172/1/012018.

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Mamatha, U. "Online Hand Gesture Recognition and Classification for Deaf and Dumb". International Journal for Research in Applied Science and Engineering Technology 9, n. VI (30 giugno 2021): 4402–4. http://dx.doi.org/10.22214/ijraset.2021.36075.

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As sign language is used by deaf and dumb but the non-sign-language speaker cannot understand there sign language to overcome the problem we proposed this system using python. In this first we taken the some of the hand gestures are captured using the web camera. The image is pre-processed and then feature are extracted from the captured image .comparing the feature extracted image with the reference image. If matched decision is taken the displayed as a text. This helps the non-sign-language members to recognize easily by using Convolutional neural network layer (CNN) with tensor flow

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Viswanathan G, Kasi, Sathya Seelan C e S. Praveen Kumar. "A Novel Approach on Communication between Blind, Deaf and Dumb People using flex Sensors and Bluetooth". International Journal of Engineering & Technology 7, n. 3.12 (20 luglio 2018): 485. http://dx.doi.org/10.14419/ijet.v7i3.12.16165.

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The recent development in many technologies have been playing a major role in satisfying people’s lives for their daily need. But still few people are suffering due to some problems. They are blind, deaf and dumb people who are unable to communicate properly with others or among themselves. And we know that there are millions of people who are blind, deaf and dumb in this world. And we know that they use sign language to communicate but only few people can be able to understand. So this project introduces a system that can be used to improve the communication among blind, deaf and dumb people. This project introduces an idea that communication can be done using flex sensors and Bluetooth using ARDUINO boards. Flex sensors are fixed with the gloves such that it can be bent along with the movement of fingers and then it is connected to ARDUINO. Then LCD and Audio Playback Recorder module is connected to ARDUINO and then coding is done such that if flex sensor is bent, a specified message is displayed on LCD and can be played in speaker through APR module. Here coding is done using a software ARDUINO IDE. We can also send text message through android smart phone which will be displayed on LCD, this can be done by connecting Bluetooth module to ARDUINO and message can be sent through an app by connecting to Bluetooth. We are also using GPS module to track the present location which will be displayed on LCD in terms of latitude and longitudinal degrees.

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Ahuja, Ravinder, Daksh Jain, Deepanshu Sachdeva, Archit Garg e Chirag Rajput. "Convolutional Neural Network Based American Sign Language Static Hand Gesture Recognition". International Journal of Ambient Computing and Intelligence 10, n. 3 (luglio 2019): 60–73. http://dx.doi.org/10.4018/ijaci.2019070104.

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Communicating through hand gestures with each other is simply called the language of signs. It is an acceptable language for communication among deaf and dumb people in this society. The society of the deaf and dumb admits a lot of obstacles in day to day life in communicating with their acquaintances. The most recent study done by the World Health Organization reports that very large section (around 360 million folks) present in the world have hearing loss, i.e. 5.3% of the earth's total population. This gives us a need for the invention of an automated system which converts hand gestures into meaningful words and sentences. The Convolutional Neural Network (CNN) is used on 24 hand signals of American Sign Language in order to enhance the ease of communication. OpenCV was used in order to follow up on further execution techniques like image preprocessing. The results demonstrated that CNN has an accuracy of 99.7% utilizing the database found on kaggle.com.

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Maity, Nabanita, e Bhim Chandra Mandal. "Creativity and impulsivity among deaf and dumb children: A correlational study". International Journal of Social Sciences 6, n. 1 (2017): 15. http://dx.doi.org/10.5958/2321-5771.2017.00002.3.

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Shaw, Suryabhan, Archana Kumari e Samir Basak. "INTERPRETER GLOVE WITH GESTURE RECOGNITION ABILITY FOR DUMB AND DEAF ONES". ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY 05, n. 01 (16 aprile 2019): 1–4. http://dx.doi.org/10.33130/ajct.2019v05i01.009.

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Shrawankar, Urmila, e Sayli Dixit. "Conversion of Tactile Sign Language into English for Deaf/Dumb Interaction". International Journal of Natural Computing Research 6, n. 1 (gennaio 2017): 53–67. http://dx.doi.org/10.4018/ijncr.2017010104.

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Natural language is the way of communication for normal human beings which includes spoken language, written and body gestures i.e. head gesture, hand gestures, facial expressions and lip motion etc. On the other hand, speech and hearing-impaired people uses sign language for communication which is not understandable for normal people thus they face problems of communication in society. In this problem interpreters are required but the human interpreters are costly and are not an efficient solution. Thus, there is a need of system which will translate the sign language into normal language which will be understandable by normal. The system proposed and explained in the paper is an efficient solution to this problem. In the system, sign recognition is done using CAMSHIFT and P2DHHM algorithm followed by Haar Cascade Classifier. After sign recognition, the language technology techniques of POS tagging and LALR parser are used to convert recognized sign words into English sentence. Till date no any system has worked on sentence framing. Results shows that this system produces 92% of accurate result which will bridge the gap between impaired and Normal people.

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Ambavane, Pritesh, Rahul Karjavkar, Hemant Pathare, Shubham Relekar, Bhavana Alte e Neeraj Kumar Sharma. "A Novel Communication System For Deaf And Dumb People using gesture". ITM Web of Conferences 32 (2020): 02003. http://dx.doi.org/10.1051/itmconf/20203202003.

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Human Beings know each other and contact with themselves through thoughts and ideas.The best way to present our idea is through speech. Some people don’t have the power of speech; the only way they communicate with others is through sign language. Now a days technology has reduced the gap through systems which can be used to change the sign language used by these people to speech. Sign language recognition (SLR) and gesture-based control are two major applications used for hand gesture recognition technologies. On the other side the controller converts the sign language in to the text and speech which gets converted with the help of text to speech conversion and analog to digital conversion. A Dumb person throughout the world uses sign language for the communication.The best way to present our idea is through speech. Some people don’t have the power of speech; the only way they communicate with others is through sign language. Now a days technology has reduced the gap through systems which can be used to change the sign language used by these people to speech. Sign language recognition (SLR) and gesture-based control are two major applications used for hand gesture recognition technologies. On the other side the controller converts the sign language in to the text and speech which gets converted with the help of text to speech conversion and analog to digital conversion. A Dumb person throughout the world uses sign language for the communication.

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Wazalwar, Sampada. "Online Healthcare Consultation System for Deaf & Dumb During Pandemic Situation". Bioscience Biotechnology Research Communications 13, n. 14 (25 dicembre 2020): 213–16. http://dx.doi.org/10.21786/bbrc/13.14/50.

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Woll, Bencie, e Jechil S. Sieratzki. "Leftward Cradling Bias, Prosodic Speech, and Deafness: The Deaf Are Not Dumb". Journal of Genetic Psychology 163, n. 1 (marzo 2002): 126–28. http://dx.doi.org/10.1080/00221320209597973.

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Miller, Don A. "d/DEAF and d/DUMB: A Portrait of a Deaf Kid as a Young Superhero by Joseph Michael Valente". Sign Language Studies 13, n. 3 (2013): 423–25. http://dx.doi.org/10.1353/sls.2013.0011.

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Viridarsky, S. T. "From the Midwife Institute. The case of cutting the long-junction." Journal of obstetrics and women's diseases 8, n. 1 (14 settembre 2020): 23–27. http://dx.doi.org/10.17816/jowd8123-27.

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On November 26, 1893, at 2 o'clock in the afternoon, she entered the Midwife Institute for delivery, a petty bourgeois woman of St. Petersburg province Elena Koperskaya, Orthodox. 25 years old, unmarried, primiparous. The woman in labor is deaf and dumb. From the information collected regarding the previous state of her health, the following became clear: a patient was born in St. Petersburg, where she spent her childhood.

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Citri, A. "The deaf and the dumb: the biology of ErbB-2 and ErbB-3". Experimental Cell Research 284, n. 1 (10 marzo 2003): 54–65. http://dx.doi.org/10.1016/s0014-4827(02)00101-5.

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Montgomery, Bert. "Deaf, Dumb and Blind Churches: James Meets the Who (Jas 2:14–17)". Review & Expositor 108, n. 3 (agosto 2011): 439–44. http://dx.doi.org/10.1177/003463731110800310.

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Soares, M. O. "Is the QALY blind, deaf and dumb to equity? NICE's considerations over equity". British Medical Bulletin 101, n. 1 (13 febbraio 2012): 17–31. http://dx.doi.org/10.1093/bmb/lds003.

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Gomathi, T. "Audio Visual Reception of American Sign Language for Blind, Deaf and Dumb People". International Journal for Research in Applied Science and Engineering Technology 9, n. VI (20 giugno 2021): 1918–23. http://dx.doi.org/10.22214/ijraset.2021.35263.

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The computer recognition of sign language is an important process for enabling communication with the visually and hearing impaired people. This proposed project introduces an efficient way of computer recognition of sign languageby using a simplified method by the use of an accelerometer sensor which is a three axis sensor and a voice IC. The main objective of our project is to convert the sign language into a voice format and display the corresponding message on the LCD screen. The basic idea of this project is to have accelerometer sensors attached to the gloves worn by the impaired person. When the person flexes his/her hand for the pre-coded commands, the accelerometer sensors senses the change due to the angular movement of fingers and produces a corresponding output voltage. The sensed analog signal is converted to digital signal by ADC and transmits it to the voice IC via a microcontroller. The objective of the microcontroller is to perform the matching of the obtained hex-code with its corresponding pre-coded commands using Keil software. Once the code is matched with its pre-coded commands the output is delivered through a speaker via a voice IC and the command is also displayed in a LCD screen.

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Kitzel, Mary E. "Creating a Deaf place: the development of the Asylum for Deaf and Dumb Poor Children in the early nineteenth century". Journal of Cultural Geography 34, n. 2 (30 marzo 2017): 149–69. http://dx.doi.org/10.1080/08873631.2017.1305522.

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Smirnov, S. A. "Smart Body or the Problem of Human Corporeality Development in the Context of Outsourced Life. Paper Two". Cultural-Historical Psychology 12, n. 4 (2016): 100–112. http://dx.doi.org/10.17759/chp.2016120410.

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This paper continues to explore the problem of formation of non-organic body of personality touched upon in the previous part. The author shows how this problem is addressed in the works of E.V. Ilyenkov, B. Spinoza and L.S. Vygotsky and, in particular, in the works of D.B. Elkonin and B.D. Elkonin who introduced the concepts of ‘mediatory action’ and ‘event of action’, crucial for the understanding of personality construction. In the final part of the paper the author reviews the practices of blind, deaf and dumb pedagogy as the phenomenon of cultural development and cultural corporeality. Working with blind, deaf and dumb children proves the correctness of the cultural-historical concept aimed at tool/activity-based character of personality structure formation that may well be described in terms of smart corporeality. Without such practices of exploration and acquisition of his/her own behavior the individual becomes a functionally disabled person. Thus the author considers the practice of cultural development an anthropological alternative to the trend of outsourcing that implies the individual’s rejection of his/her basic cultural functions and practices. And this alternative acts as a response to the challenge of the increasing cultural, functional and personal disabilities. The research was conducted with the assistance of the Russian Science Foundation (project №14-18-03087 “Designing Non- classical Anthropology. New Human Ontology”).

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R, Sharanya. "Sign Voice Bi-Directional Communication System (SVBi) for Blind, Deaf/Dumb and Normal People". International Journal for Research in Applied Science and Engineering Technology 7, n. 5 (31 maggio 2019): 2500–2508. http://dx.doi.org/10.22214/ijraset.2019.5414.

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Coolidge, Grace E. ""Neither Dumb, Deaf, nor Destitute of Understanding": Women as Guardians in Early Modern Spain". Sixteenth Century Journal 36, n. 3 (1 ottobre 2005): 673. http://dx.doi.org/10.2307/20477485.

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Rajam, P. Subha, e G. Balakrishnan. "Recognition of Tamil Sign Language Alphabet using Image Processing to aid Deaf-Dumb People". Procedia Engineering 30 (2012): 861–68. http://dx.doi.org/10.1016/j.proeng.2012.01.938.

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