Aarthy Suganthi Kani

@tjohncollege.com

Assistant Professor
T John Institute of Technology

Aarthy Suganthi Kani


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https://researchid.co/aarthyjohn

RESEARCH, TEACHING, or OTHER INTERESTS

Engineering, Computer Vision and Pattern Recognition
2

Scopus Publications

6

Scholar Citations

2

Scholar h-index

Scopus Publications

  • Attention deficit hyperactivity disorder (ADHD) detection for IoT based EEG signal
    J. Aarthy Suganthi Kani, S. Immanuel Alex Pandian, Anitha J, R. Harry John Asir
    Computer Methods in Biomechanics and Biomedical Engineering, 2024
    ADHD is a prevalent childhood behavioral problem. Early ADHD identification is essential towards addressing the disorder and minimizing its negative impact on school, career, relationships, as well as general well-being. The present ADHD diagnosis relies primarily on an emotional assessment which can be readily influenced by clinical expertise and lacks a basis of objective markers. In this paper, an innovative IoT based ADHD detection is proposed using an EEG signal. To the input EEG signal, the min-max normalization technique is processed. Features are extracted as the subsequent step, where improved fuzzy feature, in which the entropy is estimated to increase the effectiveness of recognizing the vector along with, fractal dimension, wavelet transform and non-linear features are extracted. Also, proposes the new hybrid PUDMO algorithm to select the optimal features from the extracted feature set. Subsequently, the selected features are fed to the proposed hybrid detection system that including IDBN and LSTM classifier to detect whether it is ADHD or not. Further, the weights of both classifiers are tuned optimally as per the hybrid PUDMO algorithm to enhance the detection performance. The PUDMO achieved an accuracy of 0.9649 in the best statistical metric, compared to the SLO's 0.8266, SOA's 0.8201, SMA's 0.8060, BRO's 0.8563, DE's 0.8083, POA's 0.8537, and DMOA's 0.8647, respectively. Thus, the assessments and detection help the clinicians to take appropriate decision.
  • A Systematic Review on Attention Deficit Hyperactivity Disorder (ADHD) Detection Model
    J. Aarthy Suganthi Kani, S. Immanuel Alex Pandian, J. Anitha, R Harry John Asir
    Proceedings of 2023 IEEE Technology and Engineering Management Conference Asia Pacific Temscon Aspac 2023, 2023
    The most prevalent neurodevelopmental condition that impact in the kid stage and lasts into adulthood is ADHD. ADHD in children is often recognized and treated between the ages of 6 and 12. Although the exact origin of ADHD is unknown, it is believed that genetics, neurochemical deficits, brain network dysfunctions (such dopamine deficiency), and environmental factors all play a part. It is widely demonstrated that environmental and genetic variables, such as maternal smoking, alcohol or drug abuse, and psychological issues during pregnancy are the main causes of ADHD. Children with ADHD frequently have lower brain volumes and dysfunctional frontal and parietal cortices. This survey intends to prepare a review on different ADHD detection models adoptedin the recent 25 papers. The review includes the following (i) reviewing different ADHD detection models in terms of machine learning and deep learning strategies, (ii) Different features considered and extracted are reviewed, (iii)The datasets used in the papers arereviewed, (iv) The best performance of the modelsarereviewed, and (v) The article is concluded by identifying several research issues in the area.

RECENT SCHOLAR PUBLICATIONS

  • Strategic Cloud Selection: Aligning Workload Requirements with the Core Competencies of AWS, Azure, GCP, IBM and OCI
    K M, A Suganthi, A Sinha, S Sb
    https://doi.org/10.1109/icicnis66685.2025.11315798 , 2025
    2025.0
  • A Survey on Finger Vein Authentication System: A Secure Biometric Identification Method
    JAS Kani, P Varshini, B Supriya, HR Prajwal
    2025 6th International Conference on IoT Based Control Networks and … , 2025
    2025.0
  • Attention deficit hyperactivity disorder (ADHD) detection for IoT based EEG signal
    JAS Kani, SIA Pandian, RHJ Asir
    Computer Methods in Biomechanics and Biomedical Engineering 27 (16), 2269-2287 , 2024
    2024.0
    Citations: 1
  • A Systematic Review on Attention Deficit Hyperactivity Disorder (ADHD) Detection Model
    JAS Kani, SIA Pandian, J Anitha, RHJ Asir
    2023 IEEE Technology & Engineering Management Conference-Asia Pacific … , 2023
    2023.0
  • Zone Based Vehicle Speed Control System
    JAS Kani, APV Amal, MD Monisha, S Shuchika, SBA Sarath
    T. John Institute of Technology , 2023
    2023.0
    Citations: 2
  • Simple Multiple Choice Questions on Artificial Intelligence Techniques
    EP V.S.Prabhin., J.Aarthy Suganthi Kani.
    2023.0
  • IoT enabled RFID based Smart electric vehicle charging station for smart city application
    DSHPMJASKMBNJDMGMYPDAVMSNMSVMK Mallela
    IN Patent 46/2,022 , 2022
    2022.0
  • Wireless Glove for Hand Gesture Acknowledgment: Sign Language to Discourse Change Framework in Territorial Dialect
    JASKAR Shahrukh Javed1*, Ghousia Banu S1
    Robotics & Automation Engineering Journal 3 (2), 50-57 , 2018
    2018.0
    Citations: 3
  • PEAK CANCELLATION CREST FACTOR REDUCTION TECHNIQUE FOR OFDM SIGNALS
    ASKJAKD VINAY REDDY N1
    IMPACT: International Journal of Research in Engineering & Technology … , 2015
    2015.0
  • IoT based Remote health Monitoring and Patients’ early treatment using Arduino Uno
    E Adama
  • Detection of ADHD Based on Iot
    MAJS Kani, PV Amal, D Monisha, S Shuchika, SB AS

MOST CITED SCHOLAR PUBLICATIONS

  • Wireless Glove for Hand Gesture Acknowledgment: Sign Language to Discourse Change Framework in Territorial Dialect
    JASKAR Shahrukh Javed1*, Ghousia Banu S1
    Robotics & Automation Engineering Journal 3 (2), 50-57 , 2018
    2018.0
    Citations: 3
  • Zone Based Vehicle Speed Control System
    JAS Kani, APV Amal, MD Monisha, S Shuchika, SBA Sarath
    T. John Institute of Technology , 2023
    2023.0
    Citations: 2
  • Attention deficit hyperactivity disorder (ADHD) detection for IoT based EEG signal
    JAS Kani, SIA Pandian, RHJ Asir
    Computer Methods in Biomechanics and Biomedical Engineering 27 (16), 2269-2287 , 2024
    2024.0
    Citations: 1
  • Strategic Cloud Selection: Aligning Workload Requirements with the Core Competencies of AWS, Azure, GCP, IBM and OCI
    K M, A Suganthi, A Sinha, S Sb
    https://doi.org/10.1109/icicnis66685.2025.11315798 , 2025
    2025.0
  • A Survey on Finger Vein Authentication System: A Secure Biometric Identification Method
    JAS Kani, P Varshini, B Supriya, HR Prajwal
    2025 6th International Conference on IoT Based Control Networks and … , 2025
    2025.0
  • A Systematic Review on Attention Deficit Hyperactivity Disorder (ADHD) Detection Model
    JAS Kani, SIA Pandian, J Anitha, RHJ Asir
    2023 IEEE Technology & Engineering Management Conference-Asia Pacific … , 2023
    2023.0
  • Simple Multiple Choice Questions on Artificial Intelligence Techniques
    EP V.S.Prabhin., J.Aarthy Suganthi Kani.
    2023.0
  • IoT enabled RFID based Smart electric vehicle charging station for smart city application
    DSHPMJASKMBNJDMGMYPDAVMSNMSVMK Mallela
    IN Patent 46/2,022 , 2022
    2022.0
  • PEAK CANCELLATION CREST FACTOR REDUCTION TECHNIQUE FOR OFDM SIGNALS
    ASKJAKD VINAY REDDY N1
    IMPACT: International Journal of Research in Engineering & Technology … , 2015
    2015.0
  • IoT based Remote health Monitoring and Patients’ early treatment using Arduino Uno
    E Adama
  • Detection of ADHD Based on Iot
    MAJS Kani, PV Amal, D Monisha, S Shuchika, SB AS