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Related Concept Videos

Somatosensation01:33

Somatosensation

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The somatosensory system relays sensory information from the skin, mucous membranes, limbs, and joints. Somatosensation is more familiarly known as the sense of touch. A typical somatosensory pathway includes three types of long neurons: primary, secondary, and tertiary. Primary neurons have cell bodies located near the spinal cord in groups of neurons called dorsal root ganglia. The sensory neurons of ganglia innervate designated areas of skin called dermatomes.
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Sensory Functions of the Skin01:16

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The skin is the largest organ of the human body and plays a crucial role in our sensory perception. It contains a vast network of sensory receptors that contribute to the skin's protective function by perceiving physical, biological, and environmental cues and generating relevant responses.
There are two main categories of receptors on the skin: capsulated and non-capsulated. The non-capsulated ones are mainly the pain receptors. The capsulated ones can be further categorized based on the...
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Motor and Sensory Areas of the Cortex01:14

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The cerebral cortex, the brain's outermost layer, is pivotal in processing complex cognitive tasks, emotions, and various sensory inputs and executing voluntary motor activities. This intricate structure is divided into three primary functional areas: the motor areas, sensory areas, and association areas.
Motor Areas
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Sensory Perception: Organization of the Somatosensory System01:11

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The somatosensory system is the central and peripheral nervous system component that senses and processes touch, pressure, pain, temperature, and body position or proprioception. The process of sensation takes place at three levels:
The receptor level:
The receptor level is the first stage of sensation. It involves the detection of a stimulus by specialized sensory receptors. The stimulus must arrive within the receptor's receptive field. Next, the receptor converts the energy of the...
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Introduction to Special Senses01:26

Introduction to Special Senses

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Sensory receptors play an integral part in comprehending our external and internal environments. They receive diverse stimuli, converting them into the nervous system's electrochemical signals. This conversion occurs as the stimulus alters the sensory neuron's cell membrane potential, instigating the generation of an action potential. This action potential is subsequently transmitted to the central nervous system (CNS), which integrates with other sensory data or higher cognitive...
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Somatosensory, Motor, and Association Cortex01:23

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The somatosensory cortex in the parietal lobes is crucial for interpreting sensory data such as touch, temperature, and proprioception. The somatosensory cortex, situated in the parietal lobes, plays a vital role in interpreting sensory information like touch, temperature, and proprioception—awareness of body position. This specialized brain region features an organized structure wherein neurons at the top primarily process sensations originating from the lower body. In contrast, those at...
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Related Experiment Video

Updated: May 2, 2026

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
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Robust human locomotion and localization activity recognition over multisensory.

Danyal Khan1, Mohammed Alonazi2, Maha Abdelhaq3

  • 1Department of Computer Science, Air University, Islamabad, Pakistan.

Frontiers in Physiology
|March 7, 2024
PubMed
Summary

This study introduces an advanced human activity recognition (HAR) method using smartphone sensors and deep learning. The system accurately identifies locomotion and indoor/outdoor activities, showing potential for real-world applications.

Keywords:
GPSGPS sensorconvolutional neural networkconvolutional neural network (CNN)deep learninghuman activity recognitionlong short-term memory human activity recognitionsmart IMU

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Area of Science:

  • Computer Science
  • Machine Learning
  • Signal Processing

Background:

  • Human Activity Recognition (HAR) is crucial for healthcare, sports, robotics, and security.
  • Wearable devices like Inertial Measurement Units (IMUs) and ambient sensors enable advanced HAR.
  • Existing methods require improved accuracy and efficiency in classifying diverse human activities.

Purpose of the Study:

  • To develop an advanced methodology for human activity and localization recognition.
  • To leverage smartphone sensor data (IMU, Ambient, GPS, Audio) for enhanced HAR.
  • To explore state-of-the-art deep learning techniques for accurate activity classification.

Main Methods:

  • Utilized the Opportunity and Extrasensory benchmark datasets.
  • Incorporated novel feature extraction for signal, GPS, and audio data.
  • Employed Convolutional Neural Networks (CNNs) for indoor/outdoor activity recognition and Long Short-Term Memory (LSTM) networks for locomotion activity recognition.
  • Developed a hybrid system combining machine learning and deep learning features.

Main Results:

  • Achieved 97% accuracy for locomotion activity on the Opportunity dataset.
  • Achieved 89% accuracy for locomotion activity on the Extrasensory dataset.
  • Attained 96% accuracy for indoor/outdoor activity recognition on the Extrasensory dataset.

Conclusions:

  • The proposed methodology demonstrates high efficiency and accuracy in human activity and localization recognition.
  • The hybrid system effectively enhances HAR performance by integrating diverse sensor data and learning techniques.
  • The findings show significant potential for real-world applications in various domains.