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Sensing Technologies and IoT for Ambient Assisted Living

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (25 August 2023) | Viewed by 10811

Special Issue Editor

1. Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo 135-0064, Japan
2. Department of Mechanical Engineering, Tokyo Institute of Technology, 2-12-1, O-okayama, Meguro-ku, Tokyo 152-8552, Japan
Interests: intelligent mechanics; mechanical systems (human-machine systems); environment sensorizing system; digital human model; digital human presentation

Special Issue Information

Dear Colleagues,

There is a formidable need to develop life-function-resilient services that can maintain and improve safety, comfort, and social participation regardless of changes in life functions. To this end, technology helping to understand ever-changing life is required. In the past, many studies on ergonomic human behavior and daily living understanding were conducted by collecting data from a large number of people in a short period at laboratories, specialized institutions, and social events. However, it was difficult to detect individual changes sensitively and understand the situation considering the detection and the individual’s situation. On the other hand, with the development of AI, and IoT in recent years, not only is ergonomic understanding using socially collected big data, but also a non-ergonomic understanding becomes possible: the detection of the individual change based on long-term time-series data measurements of individuals. In this Special Issue, we are looking for novel sensing techniques and data science methods related to the non-ergonomic understanding of human behavior and daily lives.

Prof. Dr. Yoshifumi Nishida
Guest Editor

Manuscript Submission Information

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Keywords

  • IoT
  • long-term monitoring
  • individual monitoring
  • smart home
  • behavior understanding at home
  • sensor network
  • elderly people support

Published Papers (5 papers)

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Research

33 pages, 9489 KiB  
Article
Augmented-Reality Presentation of Household Sounds for Deaf and Hard-of-Hearing People
by Takumi Asakura
Sensors 2023, 23(17), 7616; https://doi.org/10.3390/s23177616 - 02 Sep 2023
Viewed by 1055
Abstract
Normal-hearing people use sound as a cue to recognize various events that occur in their surrounding environment; however, this is not possible for deaf and hearing of hard (DHH) people, and in such a context they may not be able to freely detect [...] Read more.
Normal-hearing people use sound as a cue to recognize various events that occur in their surrounding environment; however, this is not possible for deaf and hearing of hard (DHH) people, and in such a context they may not be able to freely detect their surrounding environment. Therefore, there is an opportunity to create a convenient device that can detect sounds occurring in daily life and present them visually instead of auditorily. Additionally, it is of great importance to appropriately evaluate how such a supporting device would change the lives of DHH people. The current study proposes an augmented-reality-based system for presenting household sounds to DHH people as visual information. We examined the effect of displaying both the icons indicating sounds classified by machine learning and a dynamic spectrogram indicating the real-time time–frequency characteristics of the environmental sounds. First, the issues that DHH people perceive as problems in their daily lives were investigated through a survey, suggesting that DHH people need to visualize their surrounding sound environment. Then, after the accuracy of the machine-learning-based classifier installed in the proposed system was validated, the subjective impression of how the proposed system increased the comfort of daily life was obtained through a field experiment in a real residence. The results confirmed that the comfort of daily life in household spaces can be improved by combining not only the classification results of machine learning but also the real-time display of spectrograms. Full article
(This article belongs to the Special Issue Sensing Technologies and IoT for Ambient Assisted Living)
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17 pages, 15730 KiB  
Article
IoT Smart Flooring Supporting Active and Healthy Lifestyles
by Federico Cocconcelli, Guido Matrella, Niccolò Mora, Ion Casu, David Alejandro Vargas Godoy and Paolo Ciampolini
Sensors 2023, 23(6), 3162; https://doi.org/10.3390/s23063162 - 16 Mar 2023
Cited by 2 | Viewed by 1931
Abstract
The lack of physical exercise is among the most relevant factors in developing health issues, and strategies to incentivize active lifestyles are key to preventing these issues. The PLEINAIR project developed a framework for creating outdoor park equipment, exploiting the IoT paradigm to [...] Read more.
The lack of physical exercise is among the most relevant factors in developing health issues, and strategies to incentivize active lifestyles are key to preventing these issues. The PLEINAIR project developed a framework for creating outdoor park equipment, exploiting the IoT paradigm to build “Outdoor Smart Objects” (OSO) for making physical activity more appealing and rewarding to a broad range of users, regardless of their age and fitness. This paper presents the design and implementation of a prominent demonstrator of the OSO concept, consisting of a smart, sensitive flooring, based on anti-trauma floors commonly found in kids playgrounds. The floor is equipped with pressure sensors (piezoresistors) and visual feedback (LED-strips), to offer an enhanced, interactive and personalized user experience. OSOs exploit distributed intelligence and are connected to the Cloud infrastructure by using a MQTT protocol; apps have then been developed for interacting with the PLEINAIR system. Although simple in its general concept, several challenges must be faced, related to the application range (which called for high pressure sensitivity) and the scalability of the approach (requiring to implement a hierarchical system architecture). Some prototypes were fabricated and tested in a public environment, providing positive feedback to both the technical design and the concept validation. Full article
(This article belongs to the Special Issue Sensing Technologies and IoT for Ambient Assisted Living)
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25 pages, 1541 KiB  
Article
A 2D-Lidar-Equipped Unmanned Robot-Based Approach for Indoor Human Activity Detection
by Mondher Bouazizi, Alejandro Lorite Mora and Tomoaki Ohtsuki
Sensors 2023, 23(5), 2534; https://doi.org/10.3390/s23052534 - 24 Feb 2023
Cited by 4 | Viewed by 4329
Abstract
Monitoring the activities of elderly people living alone is of great importance since it allows for the detection of when hazardous events such as falling occur. In this context, the use of 2D light detection and ranging (LIDAR) has been explored, among others, [...] Read more.
Monitoring the activities of elderly people living alone is of great importance since it allows for the detection of when hazardous events such as falling occur. In this context, the use of 2D light detection and ranging (LIDAR) has been explored, among others, as a way to identify such events. Typically, a 2D LIDAR is placed near the ground and collects measurements continuously, and a computational device classifies these measurements. However, in a realistic environment with home furniture, it is hard for such a device to operate as it requires a direct line of sight (LOS) with its target. Furniture will block the infrared (IR) rays from reaching the monitored person thus limiting the effectiveness of such sensors. Nonetheless, due to their fixed location, if a fall is not detected when it happens, it cannot be detected afterwards. In this context, cleaning robots present a much better alternative given their autonomy. In this paper, we propose to use a 2D LIDAR mounted on top of a cleaning robot. Through continuous movement, the robot is able to collect distance information continuously. Despite having the same drawback, by roaming in the room, the robot can identify if a person is laying on the ground after falling, even after a certain period from the fall event. To achieve such a goal, the measurements captured by the moving LIDAR are transformed, interpolated, and compared to a reference state of the surroundings. A convolutional long short-term memory (LSTM) neural network is trained to classify the processed measurements and identify if a fall event occurs or has occurred. Through simulations, we show that such a system can achieve an accuracy equal to 81.2% in fall detection and 99% in the detection of lying bodies. Compared to the conventional method, which uses a static LIDAR, the accuracy reaches for the same tasks 69.4% and 88.6%, respectively. Full article
(This article belongs to the Special Issue Sensing Technologies and IoT for Ambient Assisted Living)
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12 pages, 4844 KiB  
Article
Assessing Handrail-Use Behavior during Stair Ascent or Descent Using Ambient Sensing Technology
by Yusuke Miyazaki, Kohei Shoda, Koji Kitamura and Yoshifumi Nishida
Sensors 2023, 23(4), 2236; https://doi.org/10.3390/s23042236 - 16 Feb 2023
Viewed by 1406
Abstract
The increasing geriatric population across the world has necessitated the early detection of frailty through the analysis of daily-life behavioral patterns. This paper presents a system for ambient, automatic, and the continuous measurement and analysis of ascent and descent motions and long-term handrail-use [...] Read more.
The increasing geriatric population across the world has necessitated the early detection of frailty through the analysis of daily-life behavioral patterns. This paper presents a system for ambient, automatic, and the continuous measurement and analysis of ascent and descent motions and long-term handrail-use behaviors of participants in their homes using an RGB-D camera. The system automatically stores information regarding the environment and three-dimensional skeletal coordinates of the participant only when they appear within the camera’s angle of view. Daily stair ascent and descent motions were measured in two houses: one house with two participants in their 20s and two in their 50s, and another with two participants in their 70s. The recorded behaviors were analyzed in terms of the stair ascent/descent speed, handrail grasping points, and frequency determined using the decision tree algorithm. The participants in their 70s exhibited a decreased stair ascent/descent speed compared to other participants; those in their 50s and 70s exhibited increased handrail usage area and frequency. The outcomes of the study indicate the system’s ability to accurately detect a decline in physical function through the continuous measurement of daily stair ascent and descent motions. Full article
(This article belongs to the Special Issue Sensing Technologies and IoT for Ambient Assisted Living)
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11 pages, 1402 KiB  
Article
Individuals with and without Visual Impairments Use a Force Feedback Device to Identify the Friction and Hardness of Haptic Surfaces
by Konstantinos Papadopoulos, Eleni Koustriava, Evangelia Georgoula and Vaia Kalpia
Sensors 2022, 22(24), 9745; https://doi.org/10.3390/s22249745 - 12 Dec 2022
Cited by 1 | Viewed by 1327
Abstract
The general purpose of this study is to promote access to haptic virtual environments. Using a haptic device, people with and without visual impairments (VI) are able to feel different textures and compare these textures based on different surface properties, i.e., friction and [...] Read more.
The general purpose of this study is to promote access to haptic virtual environments. Using a haptic device, people with and without visual impairments (VI) are able to feel different textures and compare these textures based on different surface properties, i.e., friction and hardness. The objectives of this study were to examine the following: (a) whether the variables of friction and hardness were identifiable through the Touch device (Phantom Omni) and could therefore function as 3D haptic variables; (b) if there were differences between people with VI and sighted individuals in terms of their performance; (c) the differences that should exist between the values of each variable so that the virtual surfaces could be identified as different to each other; and (d) if the individual characteristics of participants have an impact on their performance. The results showed that it is necessary to use surfaces which are differentiated based on the degree of friction and hardness because the haptic properties of a virtual object are then better perceived. Individuals with VI need more time and more effort to understand friction and hardness, respectively. With the motivation of increasing access to object perception for people with VI in a virtual environment, accessibility advisors and experts can extract useful information for the development of functional and efficient 3D objects for haptic perception. Full article
(This article belongs to the Special Issue Sensing Technologies and IoT for Ambient Assisted Living)
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