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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 04 Issue: 07 | July -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 404
Applications Of Sensors To Detect The Behavior Of Human. A Survey
Paper
Avtansh Singh1,Vandana Vikas Thakare2
1Student, Dept. of Electronics and Communication Engineering, Madhav Institute Of Technology and Science,
Gwalior, India
2Associate Professor, Dept. of Electronics and Communication Engineering, Madhav Institute Technology and
Science ,Gwalior, India
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - A decade years ago, there is alotofResearchesas
well as investigation has been conducted in the area of real-
time emotion recognition of a humans like Heart rate,
Breathing rate, Body Temperature, skin conductance etc.
Emotion recognition has a significant applications in
education, medicine, technologies and human-machine
interaction. The present paper reveals the researchesthathas
been conducted related to the application of sensors,
automation, bio-signaling, and controlling ways over to the
behavior/feelings of humans.
Key Words: bio-signaling, automation, Sensors, Emotion
recognition, human machine interaction
1.INTRODUCTION
In the recent times, there is a lot of excellent sessions has
been held at the IEEE which stressed over the design of bio-
processed signaling circuits and systems for sensing (e.g.
real-time visual, auditory and tactile processing) With the
important and crucial steps are taken for the development
and design of these systems, there is a lot of integration of
techs taken for the design towardsminglingofthesesystems
into applications, such as investigation, snooping etc. The
main aim of this session is to merges the researchers taken
for the automation, sensing and actuation.
2. RESEARCH CHALLENGES
The stressed paper represents the three research reported
that are combine expertise both in areas that are covered as
a wearable sensory systems, Communication by gesture in
emergency and a Kit supporting multiple bio-signals
acquisition and a certain areas which are not commonly
seen, such as robotics, nanotech, neurotech.etc. [1-3]The
survey paper, mainly suppress the three invited papers in
the session and then reviews the past work in the escalation
of bio-processed signaling circuits and systems for sensing
as well as some relatively initial work that has been done to
amalgamate these systems into applications fortheresearch
works. The relative works explodes the identification of
human behavior in certain condition. It leads to understand
the feelings which plays important role for knowing the
individual.
2.1 A Wearable device Physical and Emotion Health
Monitoring.
The author Rubin Dias stressed over Wireless Body Sensor
Nodes (WBSNs) [5-6]. The WBSNs was an embedded sensor
platforms for bio-signal acquisition. Author offer a
compelling solution for long-term monitoring of subject,
presenting little discomfort for the subjects and requiring
minimal supervision from medical staff. Proposed WBSNs
was able to acquire and wirelessly transmit different bio-
signals (e.g. blood pressure, pulse and electrocardiograms
[7]. In addition to acquisition and wireless transmission of
bio-signals, state-of-the-art WBSNs embedded advanced
processing applications, able to automatically retrieve
diagnostic information from the acquired data.[8] The
presented work as shown in Figure.1
.
Fig-1 Device for physiological signal acquisition.
Device can be attached behind a phone, and the metal pads
touched by the user or can be attached using a chest strap
.The introduced architecture of a multi-tier telemedicine
system comprised of strategically placed bio-sensors on a
human body capable of collecting vital medical statistics
(such as heart rate and blood pressure) and transmitting
them (wired or wirelessly)over multiple hops to a remote
medical server at a caregiver’s location thereby taking
telemedicine from the desktop to roaming.
2.2- Communication by gesture in personal emergency
response system.
Data glove was an electrode arrayembeddedglovesimilarto
the conventional glove worn on hands, but made with
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 04 Issue: 07 | July -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 405
stretchable material like lycra. It facilitates in sensing and
producing gesture signals from the hand of the user. The
typical data glove and its electrode positions are shown in
Figure. 2. It was a novel utility device with a new dimension
in the field of medicine and healthcare. When the
conventional input devices offer limited degrees of freedom
the gloves are offering
Fig.2 Data glove and electrode position.
multiple degree of freedom for each finger as well as to the
hand. It also allows the user to communicate with the
computer to greater[12]. The data glove used 5DT model,
and was designed for the purpose of modern motioncapture
and animation professionals.Data fromfivehealthysubjects,
including two female subjects, have been taken into
consideration, and their average age was 19.5 years
2.3- Smart Transmission Scheme For Emergency Data
From A Network Of Bio Sensors On Human Body.
Author Ali Abbas vohra presenteda researchovera Wireless
Body Area Network (WBAN) which was a network of
wearable devices (mostly sensors) that collect vital
biostatistics (such as heart rate, blood pressure, and ECG).
The devices may had intelligent computing capabilities;
however, the WBAN needs to interact with a medical
practitioner’s facility[11]. The paper required necessitates
the design of a data communication system that meshes the
WBAN with current Wide Area Networks (WAN).
Fig.3 Wireless body area networking.
The WBAN primarily consists of tiny wearable sensors that
were capable of continuous data (biostatistics) acquisition.
The data transmitted to a local access point which might be
co-located with the user’s mobile phone fromwhichthe data
can be transferred through the Internet. In which a two-way
communication also be envisioned. An adequate feedback
from the medical practitioner could be transmitted via the
same route to the sensors or the access point. The paper
focused on developing a Medium Access Control (MAC)
protocol for the WBAN.MAC schemefacilitatessuchdynamic
behavior by the system.[13] The two primary requirements
were: (a) fast and reliable data transmission and (b) low
power since the sensors were wearable.
2.4- Homecare Kit supporting multiple bio-signals
acquisition and analysis in daily life.
Author Seol young Jeong represented a homecare kit
platform that can support the medical care service. In the
proposed platform, the homecare kit consists of wearable
devices with embedded biosensors: Accelerometer(ACC),
photoplethysmograph (PPG)/ blood oxygen saturationlevel
(SpO2), Breathing, electrocardiogram (ECG); the user can
easily wear and use the homecare kit for measuring the bio-
signal in daily life or while sleeping [14]. The ACC data
recognize the user’s movementundersleeporwhenrunning
or walking. Hence, during these activities, Seol young jeong
FIG.3 Home care kit and wearing example.
gives a reasonable solution to hold the signal measurement
in order to avoid noisy data accumulation. In the paper a
sleep apnea subject actually wore homecare kit and
polysomnography equipment simultaneously in the
hospital[15]. Then it evaluated the equipment equivalence
based on the analysis result and acquisition bio-signal. In
which author tries, if the breath signal of the patient under
sleep was flat for a period of time because ofsleepapnea,the
SpO2 value of the patient becomes lower[16]. In addition,
diagnostic tests were expensive, and the booking was time
consuming.
3. PROPOSED SYSTEM
As a continuous changes occur in the circuit architectures
for processing data received from the sensors, the next
factual step is the implementation of these systems into an
embedded systems. The stressed paper reviews the work
that has been done in a printed circuit board systems. In a
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 04 Issue: 07 | July -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 406
PCB, sensor and central computing system build with the
application of embedded systems. Obstacleavoidancebased
on visual information has received much attention. Due to
the simplicity of circuits based on such type models have
been studied for this application. Biologically algorithm for
processing systems are more complex systems e.g. face
recognition, body motion recognition system. In the current
era, it takes lot of attention based tracking, snooping ,
identify various behavior and feelings. Recently, lot of
gadgets are developed specially for identifying various
behavior e.g. smart watch developed by apple, Samsung,
Motorola [17]l. The stressed paper focused on the device
that are monitor the various behavior of human
simultaneous. Whilethepresentpaperfocuseduponcircuits
and bio signaling systems for that process data obtained
from sensors, it is important to note that the paper
represents an embedded systems, which is specified for a
particular task though sensors which generate signals to be
applied to controller.Thedemocircuitsperformcrucial roles
in developing appropriate behavior once data is decoded.
One of the important part that grasp the attention is the
central computing unit and GSMmodule.Byutilizingmodule
the behavioral pattern of a particular subject. All the above
processing system perform important role in number of
cases i.e. subjects in critical condition or continuous
monitoring. As the time changes its role will take place
important part in our life.
3. CONCLUSIONS
In this survey paper, we have reviewed past work in bio-
signaling system and circuits utilizing sensory data and
generating behavioral signals.Thefour papersinthissession
represents efforts to indentifying behavior of a subjects.
During this session it was observed that the average
accuracy achieved for both “happiness” and “normal”
emotions was around 83%, and both the emotions
manifested same biological characteristics
REFERENCES
[1] E. Jovanov, et al. , ”Patient Monitoring Using Personal
Area Networks of Wireless
[2] Apple Watch. Online: https://www.apple.com/watch/
[3] Jawbone UP. Online: https://jawbone.com/up/
[4] J. Parkka et al. ’Activity classification using realistic data
from wearable sensors’. In: IEEE Transactions on
Information Technology in Biomedicine 10.1 (2006), pp.
119-128. issn: 1089-7771.
[5] Y. Hao and R. Foster. ’Wireless body sensor networks for
health-monitoring applications’. In: Physiological
Measurement 29.11 (Oct. 2008), R27.
[6] F. Rincon et al. ’Development and Evaluation of
Multilead Wavelet-Based ECG Delineation Algorithms for
Embedded Wireless Sensor Nodes’. In: Information
Technology in Biomedicine, IEEE Transactionson15.6(Nov.
2011), pp. 854-863.
[7] G. H. M. Willemsen et al., ”Ambulatory monitoring of the
impedance cardiogram”, Psychophysiology, 33: 184193,
1996.
[8] CW Parott et al., ”Comparison of Changes in Ejection
Fraction to Changes in Impedance Cardiography Cardiac
Index and Systolic Time Ratio”, Congest HeartFail.10(Suppl
2) 2004:11-13.
[9]Nidal S.Kamel, Shohel Sayeed, and Grant A. Ellis, “Glove-
Based Approach to Online Signature Verification”, IEEE
Transactions on Pattern Analysis and Machine Intelligence,
Vol30,No.6,June2008.
[10] Reinhard Gentner, and Joseph Classen “Development
and evaluation of a low-cost sensor glove for assessment of
human finger movements in neurophysiologic settings”,
Journal of Neuroscience Methods, 178(2009) 138-147.
[11] Wireless Medium AccessControl (MAC)andPhysical
Layer (PHY) Specifications for Low-Rate Wireless Personal
Area Networks (WPANs) - IEEE Std 802.15.4™-2006
http://www.ieee802.org/15/pub/TG4.html
[12] Y. Hovakeemian, K. Naik and A. Nayak, “A Survey on
Dependibility in Body Area Network,” 5th International
Symposium on Medical Information and Communication
Technology, March 2011.
[13] M. R. Yuce and J. Y. Khan, “Wireless Body Area Networks:
Technology, Implementation and Applications”, PAN Stanford
Publishing, ISBN: 978-981-431-6712, 2011.
[14] S. Chernbumroong, A.S. Atkins, and H. Yu, “Activity
classification using a single wrist-worn accelerometer,” in
the 5th International Conference on Software, Knowledge
Information, Industrial Management and Applications
(SKIMA), pp.1-6, Sep. 2011.
[15] D.M. Karantonis, M.R. Narayanan, M. Mathie, N.H.
Lovell, and B.G. Celler,“Implementationofa real-timehuman
movement classifier using a triaxial

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Applications of Sensors to Detect the Behavior of Human. A Survey Paper

  • 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 04 Issue: 07 | July -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 404 Applications Of Sensors To Detect The Behavior Of Human. A Survey Paper Avtansh Singh1,Vandana Vikas Thakare2 1Student, Dept. of Electronics and Communication Engineering, Madhav Institute Of Technology and Science, Gwalior, India 2Associate Professor, Dept. of Electronics and Communication Engineering, Madhav Institute Technology and Science ,Gwalior, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - A decade years ago, there is alotofResearchesas well as investigation has been conducted in the area of real- time emotion recognition of a humans like Heart rate, Breathing rate, Body Temperature, skin conductance etc. Emotion recognition has a significant applications in education, medicine, technologies and human-machine interaction. The present paper reveals the researchesthathas been conducted related to the application of sensors, automation, bio-signaling, and controlling ways over to the behavior/feelings of humans. Key Words: bio-signaling, automation, Sensors, Emotion recognition, human machine interaction 1.INTRODUCTION In the recent times, there is a lot of excellent sessions has been held at the IEEE which stressed over the design of bio- processed signaling circuits and systems for sensing (e.g. real-time visual, auditory and tactile processing) With the important and crucial steps are taken for the development and design of these systems, there is a lot of integration of techs taken for the design towardsminglingofthesesystems into applications, such as investigation, snooping etc. The main aim of this session is to merges the researchers taken for the automation, sensing and actuation. 2. RESEARCH CHALLENGES The stressed paper represents the three research reported that are combine expertise both in areas that are covered as a wearable sensory systems, Communication by gesture in emergency and a Kit supporting multiple bio-signals acquisition and a certain areas which are not commonly seen, such as robotics, nanotech, neurotech.etc. [1-3]The survey paper, mainly suppress the three invited papers in the session and then reviews the past work in the escalation of bio-processed signaling circuits and systems for sensing as well as some relatively initial work that has been done to amalgamate these systems into applications fortheresearch works. The relative works explodes the identification of human behavior in certain condition. It leads to understand the feelings which plays important role for knowing the individual. 2.1 A Wearable device Physical and Emotion Health Monitoring. The author Rubin Dias stressed over Wireless Body Sensor Nodes (WBSNs) [5-6]. The WBSNs was an embedded sensor platforms for bio-signal acquisition. Author offer a compelling solution for long-term monitoring of subject, presenting little discomfort for the subjects and requiring minimal supervision from medical staff. Proposed WBSNs was able to acquire and wirelessly transmit different bio- signals (e.g. blood pressure, pulse and electrocardiograms [7]. In addition to acquisition and wireless transmission of bio-signals, state-of-the-art WBSNs embedded advanced processing applications, able to automatically retrieve diagnostic information from the acquired data.[8] The presented work as shown in Figure.1 . Fig-1 Device for physiological signal acquisition. Device can be attached behind a phone, and the metal pads touched by the user or can be attached using a chest strap .The introduced architecture of a multi-tier telemedicine system comprised of strategically placed bio-sensors on a human body capable of collecting vital medical statistics (such as heart rate and blood pressure) and transmitting them (wired or wirelessly)over multiple hops to a remote medical server at a caregiver’s location thereby taking telemedicine from the desktop to roaming. 2.2- Communication by gesture in personal emergency response system. Data glove was an electrode arrayembeddedglovesimilarto the conventional glove worn on hands, but made with
  • 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 04 Issue: 07 | July -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 405 stretchable material like lycra. It facilitates in sensing and producing gesture signals from the hand of the user. The typical data glove and its electrode positions are shown in Figure. 2. It was a novel utility device with a new dimension in the field of medicine and healthcare. When the conventional input devices offer limited degrees of freedom the gloves are offering Fig.2 Data glove and electrode position. multiple degree of freedom for each finger as well as to the hand. It also allows the user to communicate with the computer to greater[12]. The data glove used 5DT model, and was designed for the purpose of modern motioncapture and animation professionals.Data fromfivehealthysubjects, including two female subjects, have been taken into consideration, and their average age was 19.5 years 2.3- Smart Transmission Scheme For Emergency Data From A Network Of Bio Sensors On Human Body. Author Ali Abbas vohra presenteda researchovera Wireless Body Area Network (WBAN) which was a network of wearable devices (mostly sensors) that collect vital biostatistics (such as heart rate, blood pressure, and ECG). The devices may had intelligent computing capabilities; however, the WBAN needs to interact with a medical practitioner’s facility[11]. The paper required necessitates the design of a data communication system that meshes the WBAN with current Wide Area Networks (WAN). Fig.3 Wireless body area networking. The WBAN primarily consists of tiny wearable sensors that were capable of continuous data (biostatistics) acquisition. The data transmitted to a local access point which might be co-located with the user’s mobile phone fromwhichthe data can be transferred through the Internet. In which a two-way communication also be envisioned. An adequate feedback from the medical practitioner could be transmitted via the same route to the sensors or the access point. The paper focused on developing a Medium Access Control (MAC) protocol for the WBAN.MAC schemefacilitatessuchdynamic behavior by the system.[13] The two primary requirements were: (a) fast and reliable data transmission and (b) low power since the sensors were wearable. 2.4- Homecare Kit supporting multiple bio-signals acquisition and analysis in daily life. Author Seol young Jeong represented a homecare kit platform that can support the medical care service. In the proposed platform, the homecare kit consists of wearable devices with embedded biosensors: Accelerometer(ACC), photoplethysmograph (PPG)/ blood oxygen saturationlevel (SpO2), Breathing, electrocardiogram (ECG); the user can easily wear and use the homecare kit for measuring the bio- signal in daily life or while sleeping [14]. The ACC data recognize the user’s movementundersleeporwhenrunning or walking. Hence, during these activities, Seol young jeong FIG.3 Home care kit and wearing example. gives a reasonable solution to hold the signal measurement in order to avoid noisy data accumulation. In the paper a sleep apnea subject actually wore homecare kit and polysomnography equipment simultaneously in the hospital[15]. Then it evaluated the equipment equivalence based on the analysis result and acquisition bio-signal. In which author tries, if the breath signal of the patient under sleep was flat for a period of time because ofsleepapnea,the SpO2 value of the patient becomes lower[16]. In addition, diagnostic tests were expensive, and the booking was time consuming. 3. PROPOSED SYSTEM As a continuous changes occur in the circuit architectures for processing data received from the sensors, the next factual step is the implementation of these systems into an embedded systems. The stressed paper reviews the work that has been done in a printed circuit board systems. In a
  • 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 04 Issue: 07 | July -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 406 PCB, sensor and central computing system build with the application of embedded systems. Obstacleavoidancebased on visual information has received much attention. Due to the simplicity of circuits based on such type models have been studied for this application. Biologically algorithm for processing systems are more complex systems e.g. face recognition, body motion recognition system. In the current era, it takes lot of attention based tracking, snooping , identify various behavior and feelings. Recently, lot of gadgets are developed specially for identifying various behavior e.g. smart watch developed by apple, Samsung, Motorola [17]l. The stressed paper focused on the device that are monitor the various behavior of human simultaneous. Whilethepresentpaperfocuseduponcircuits and bio signaling systems for that process data obtained from sensors, it is important to note that the paper represents an embedded systems, which is specified for a particular task though sensors which generate signals to be applied to controller.Thedemocircuitsperformcrucial roles in developing appropriate behavior once data is decoded. One of the important part that grasp the attention is the central computing unit and GSMmodule.Byutilizingmodule the behavioral pattern of a particular subject. All the above processing system perform important role in number of cases i.e. subjects in critical condition or continuous monitoring. As the time changes its role will take place important part in our life. 3. CONCLUSIONS In this survey paper, we have reviewed past work in bio- signaling system and circuits utilizing sensory data and generating behavioral signals.Thefour papersinthissession represents efforts to indentifying behavior of a subjects. During this session it was observed that the average accuracy achieved for both “happiness” and “normal” emotions was around 83%, and both the emotions manifested same biological characteristics REFERENCES [1] E. Jovanov, et al. , ”Patient Monitoring Using Personal Area Networks of Wireless [2] Apple Watch. Online: https://www.apple.com/watch/ [3] Jawbone UP. Online: https://jawbone.com/up/ [4] J. Parkka et al. ’Activity classification using realistic data from wearable sensors’. In: IEEE Transactions on Information Technology in Biomedicine 10.1 (2006), pp. 119-128. issn: 1089-7771. [5] Y. Hao and R. Foster. ’Wireless body sensor networks for health-monitoring applications’. In: Physiological Measurement 29.11 (Oct. 2008), R27. [6] F. Rincon et al. ’Development and Evaluation of Multilead Wavelet-Based ECG Delineation Algorithms for Embedded Wireless Sensor Nodes’. In: Information Technology in Biomedicine, IEEE Transactionson15.6(Nov. 2011), pp. 854-863. [7] G. H. M. Willemsen et al., ”Ambulatory monitoring of the impedance cardiogram”, Psychophysiology, 33: 184193, 1996. [8] CW Parott et al., ”Comparison of Changes in Ejection Fraction to Changes in Impedance Cardiography Cardiac Index and Systolic Time Ratio”, Congest HeartFail.10(Suppl 2) 2004:11-13. [9]Nidal S.Kamel, Shohel Sayeed, and Grant A. Ellis, “Glove- Based Approach to Online Signature Verification”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol30,No.6,June2008. [10] Reinhard Gentner, and Joseph Classen “Development and evaluation of a low-cost sensor glove for assessment of human finger movements in neurophysiologic settings”, Journal of Neuroscience Methods, 178(2009) 138-147. [11] Wireless Medium AccessControl (MAC)andPhysical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (WPANs) - IEEE Std 802.15.4™-2006 http://www.ieee802.org/15/pub/TG4.html [12] Y. Hovakeemian, K. Naik and A. Nayak, “A Survey on Dependibility in Body Area Network,” 5th International Symposium on Medical Information and Communication Technology, March 2011. [13] M. R. Yuce and J. Y. Khan, “Wireless Body Area Networks: Technology, Implementation and Applications”, PAN Stanford Publishing, ISBN: 978-981-431-6712, 2011. [14] S. Chernbumroong, A.S. Atkins, and H. Yu, “Activity classification using a single wrist-worn accelerometer,” in the 5th International Conference on Software, Knowledge Information, Industrial Management and Applications (SKIMA), pp.1-6, Sep. 2011. [15] D.M. Karantonis, M.R. Narayanan, M. Mathie, N.H. Lovell, and B.G. Celler,“Implementationofa real-timehuman movement classifier using a triaxial