Ubiquitous systems are becoming an integral part of our everyday lives. Functionality and user experience often depends on accurate, sensor-based activity recognition and interaction. Systems aiming to provide the user with assistance or to monitor their behavior and condition rely heavily on sensors and the activities and interactions that they can recognize. Providing adequate activity recognition and interaction requires consideration for particular elements: sensors that are capable of capturing relevant behavior, methods that reason about sensor readings in the context of these behaviors, and appropriate methods for assisting and interacting with the user. All of these aspects are essential and can influence the quality and suitability of the provided service.
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Is artificial intelligence (AI) taking over the world?: Are humans losing out to AI in the work place?
We are at a point in history, where it seems feasible that we create technologies that could become smarter than humans. This raises the fundamental question of what roles humans play in a future world. I argue that by using these advances in ...
We all want to remain in our own homes ...
We all want to remain in our own homes and communities as we age, and wish to be proactive in our own health and wellness. However, the challenges of aging and age-related chronic diseases force many older adults into long-term care and assisted living ...
Natural Pursuits for Eye Tracker Calibration
Although, gaze-based interaction has been investigated since the 1980s and provides promising concepts to realize cognitive systems and support universal interaction within distributed environments, the main challenges, such as the Midas touch problem [...
Respiration Rate Estimation with Depth Cameras: An Evaluation of Parameters
Depth cameras have been known to be capable of picking up the small changes in distance from users' torsos, to estimate respiration rate. Several studies have shown that under certain conditions, the respiration rate from a non-mobile user facing the ...
Fewer Samples for a Longer Life Span: Towards Long-Term Wearable PPG Analysis
Photoplethysmography (PPG) sensors have become a prevalent feature included in current wearables, as the cost and size of current PPG modules have dropped significantly. Research in the analysis of PPG data has recently expanded beyond the fast and ...
Mobile Assisted Living: Smartwatch-based Fall Risk Assessment for Elderly People
We present a novel Smartwatch-based approach, to enable Mobile Assisted Living (MAL) for users with special needs. A major focus group for this approach are elderly people. We developed a tool for caregivers applicable in home environments, nursing care,...
Analysis of a Public Repository for the Study of Automatic Fall Detection Algorithms
The use of publicly available repositories containing movement traces of real or experimental subjects is a key aspect to define an evaluation framework that allows a systematic assessment of wearable fall detection systems. This papers presents a ...
Exploring Accelerometer-based Step Detection by using a Wheeled Walking Frame
Step detection with accelerometers is a very common feature that smart wearables already include. However, when using a wheeled walking frame / rollator, current algorithms may be of limited use, since a different type of motion is being excreted. In ...
Real-Time Joint Axes Estimation of the Hip and Knee Joint during Gait using Inertial Sensors
Inertial Measurement Units (IMUs) have proven to be a promising candidate for joint kinematics assessment during human locomotion. The benefits associated with IMU-based joint angle measurements are ease of handling, flexibility and low cost. However, a ...
Attribute Representation for Human Activity Recognition of Manual Order Picking Activities
- Christopher Reining,
- Michelle Schlangen,
- Leon Hissmann,
- Michael ten Hompel,
- Fernando Moya,
- Gernot A. Fink
Semantic descriptions or attribute representations have been used successfully for object and scene recognition, and for word-spotting. However, these representations have not been explored deeply on human activity recognition (HAR). Particularly, in ...
Theodor: A Step Towards Smart Home Applications with Electronic Noses
This paper presents preliminary results of the ongoing project TheOdor which explores the potential of electronic noses that make use of commodity gas sensors (MOS, MEMS) for applications in the smarthome, for example, to classify human activities based ...
A Machine Learning Approach to Violin Bow Technique Classification: a Comparison Between IMU and MOCAP systems
Motion Capture (MOCAP) Systems have been used to analyze body motion and postures in biomedicine, sports, rehabilitation, and music. With the aim to compare the precision of low-cost devices for motion tracking (e.g. Myo) with the precision of MOCAP ...
Using Wrist-Worn Activity Recognition for Basketball Game Analysis
Game play in the sport of basketball tends to combine highly dynamic phases in which the teams strategically move across the field, with specific actions made by individual players. Analysis of basketball games usually focuses on the locations of ...
Activity Recognition using Head Worn Inertial Sensors
Human activity recognition using inertial sensors is an increasingly used feature in smartphones or smartwatches, providing information on sports and physical activities of each individual. But while the position a smartphone is worn in varies between ...
Combining off-the-shelf Image Classifiers with Transfer Learning for Activity Recognition
Human Activity Recognition (HAR) plays an important role in many real world applications. Currently, various techniques have been proposed for sensor-based "HAR" in daily health monitoring, rehabilitative training and disease prevention. However, non-...
Dense 3D Optical Flow Co-occurrence Matrices for Human Activity Recognition
In this paper, a new activity recognition technique is introduced based on the gray level co-occurrence matrices (GLCM) from a 3D dense optical flow of the input RGB and Depth videos. These matrices are one of the earliest techniques used for image ...
Human Activity Recognition Using Temporal Convolutional Network
Human activity recognition using wearable sensors is an area of interest for various domains like healthcare, surveillance etc. Various approaches have been used to solve the problem of activity recognition. Recently deep learning methods like RNNs and ...
Towards a task-driven framework for multimodal fatigue analysis during physical and cognitive tasks
This paper outlines the development of a task-driven framework for multimodal fatigue analysis during physical and cognitive tasks. While fatigue is a common symptom across several neurological chronic diseases, such as multiple sclerosis (MS), ...
IT-supported Stress Management: Mediating between Sensor Data and Individual Appraisal
People are increasingly exposed to stress these days. There are numerous possible triggers for stress, e.g. multitasking or frequent interruptions. Although stress cannot be considered fundamentally negative, high stress levels can lead to negative ...
Outlining a Novel Framework for Monitoring User's Vital Signs and Activity Data in Caregiving Facilities
Wearable sensors are consistently decreasing in size, while their computational power simultaneously rises. Current wearables enable high-quality measurements of vital signs and activity data, comparable to state-of-the-art technologies. However, they ...
Gaussian Lifted Marginal Filtering
Recently, Lifted Marginal Filtering [5] has been proposed, an approach for efficient probabilistic inference in systems with multiple, (inter-)acting agents and objects (entities). The algorithm achieves its efficiency by performing inference jointly ...
FinD: Detection of Finger Movement using Smart Watch
There were several trials to detect the movement of fingers, they necessitated special sensors, either rings or gloves, attached to the fingers. Based on the background, we have developed a system to identify the moved finger called FinD using the ...
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A practical multi-sensor activity recognition system for home-based care
To cope with the increasing number of aging population, a type of care which can help prevent or postpone entry into institutional care is preferable. Activity recognition can be used for home-based care in order to help elderly people to remain at home ...