An Improved Approach for Complex Activity Recognition in Smart Homes

Thakur, Nirmalya; Han, Chia Y.

doi:10.1007/978-3-030-22888-0_15

Cited by 16 publications

(7 citation statements)

References 13 publications

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“…The recent works of Thakur et al [37][38][39][40][41][42][43][44][45][46][47][48][49][50] have extensively contributed to the field of proposing various assistive technologies for elderly care in Smart Homes. In [50], the authors proposed a Complex Activity Based Emotion Recognition Algorithm (CABERA), for analyzing the emotional state of the user in the context of ADLs.…”

Section: Review Of Assistive Technologies In Adlsmentioning

confidence: 99%

“…In [42,43] the authors proposed approaches that can analyze the multimodal aspects of human behavior in the context of ADLs to understand user performance and provide timely assistance based on need. As an extension of their works, they proposed an improved activity recognition approach in [40], that outperforms most of the other activity recognition approaches in this field and can be readily implemented in Smart Homes. In [41], they developed a system, that can track and analyze user interactions in the context of ADLs and provide task recommendations based on context attributes for helping elderly people perform ADLs in an independent manner.…”

Section: Review Of Assistive Technologies In Adlsmentioning

confidence: 99%

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A Review of Assistive Technologies for Activities of Daily Living of Elderly

Thakur¹

2020

Elderly Care: Current Issues and Challenges

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One of the distinct features of this century has been the population of older adults which has been on a constant rise. Elderly people have several needs and requirements due to physical disabilities, cognitive issues, weakened memory and disorganized behavior, that they face with increasing age. The extent of these limitations also differs according to the varying diversities in elderly, which include age, gender, background, experience, skills, knowledge and so on. These varying needs and challenges with increasing age, limits abilities of older adults to perform Activities of Daily Living (ADLs) in an independent manner. To add to it,

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Section: Review Of Assistive Technologies In Adlsmentioning

confidence: 99%

Section: Review Of Assistive Technologies In Adlsmentioning

confidence: 99%

A Review of Assistive Technologies for Activities of Daily Living of Elderly

Thakur¹

2020

Elderly Care: Current Issues and Challenges

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“…Those activities that are crucial for one's sustenance and which one performs on a daily routine basis are known as Activities of Daily Living (ADLs). There are five broad categories of ADLs-Personal Hygiene, Dressing, Eating, Maintaining Continence, and Mobility [5].…”

Section: Introductionmentioning

confidence: 99%

Multimodal Approaches for Indoor Localization for Ambient Assisted Living in Smart Homes

Thakur

Han

2021

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This work makes multiple scientific contributions to the field of Indoor Localization for Ambient Assisted Living in Smart Homes. First, it presents a Big-Data driven methodology that studies the multimodal components of user interactions and analyzes the data from Bluetooth Low Energy (BLE) beacons and BLE scanners to detect a user’s indoor location in a specific ‘activity-based zone’ during Activities of Daily Living. Second, it introduces a context independent approach that can interpret the accelerometer and gyroscope data from diverse behavioral patterns to detect the ‘zone-based’ indoor location of a user in any Internet of Things (IoT)-based environment. These two approaches achieved performance accuracies of 81.36% and 81.13%, respectively, when tested on a dataset. Third, it presents a methodology to detect the spatial coordinates of a user’s indoor position that outperforms all similar works in this field, as per the associated root mean squared error—one of the performance evaluation metrics in ISO/IEC18305:2016—an international standard for testing Localization and Tracking Systems. Finally, it presents a comprehensive comparative study that includes Random Forest, Artificial Neural Network, Decision Tree, Support Vector Machine, k-NN, Gradient Boosted Trees, Deep Learning, and Linear Regression, to address the challenge of identifying the optimal machine learning approach for Indoor Localization.

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“…There exist multiple definitions of ADLs. A broad definition of ADL may be obtained from the work in [2], which defines ADL as the tasks and activities that a person performs for sustaining themselves on a regular and routine basis in their living environments. ADLs may be grouped into five broad types of activities: Personal Hygiene, Dressing, Eating, Maintaining Continence, and Mobility.…”

Section: Introductionmentioning

confidence: 99%

“…ADLs can occur in multiple ways based on the associated spatial and temporal features of the environment as well as the user's need, motive, intention, desire, and goals [2]. The ability to walk and move independently decreases with age due to decreased motor neuron, muscle fiber, and aerobic capacity, which limits the independence of elderly people in performing these activities [3].…”

Section: Introductionmentioning

confidence: 99%

Exoskeleton-Based Multimodal Action and Movement Recognition: Identifying and Developing the Optimal Boosted Learning Approach

Thakur¹,

Han²

2021

AAIML

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This paper makes two scientific contributions to the field of exoskeleton-based action and movement recognition. First, it presents a novel machine learning and pattern recognition-based framework that can detect a wide range of actions and movements -walking, walking upstairs, walking downstairs, sitting, standing, lying, stand to sit, sit to stand, sit to lie, lie to sit, stand to lie, and lie to stand, with an overall accuracy of 82.63%. Second, it presents a comprehensive comparative study of

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An Improved Approach for Complex Activity Recognition in Smart Homes

Cited by 16 publications

References 13 publications

A Review of Assistive Technologies for Activities of Daily Living of Elderly

A Review of Assistive Technologies for Activities of Daily Living of Elderly

Multimodal Approaches for Indoor Localization for Ambient Assisted Living in Smart Homes

Exoskeleton-Based Multimodal Action and Movement Recognition: Identifying and Developing the Optimal Boosted Learning Approach

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