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Calving is a key dairy farming event and the goal is to have deliver a live, healthy calf and mother cow. Thus knowing when a cow is going to calve is very important for a dairy farm since the necessary assistance can be provided in case of difficult calving during and after birth. Thus in this paper we propose an image technology based method for detecting calving process by analyzing the motion...
The increase in the number of elderly motivates academic researchers to develop technologies that can ensure self-sufficiency in their lives. In this research, prototype of an inexpensive video monitoring system for the elderly using a single RGB camera proposed. In the process is divided into two, namely vision and event recognition module. For event recognition, we use a hierarchical description-based...
Fall is one of the major health challenges facing the elderly adults, especially the adults with high fall risk factors. In this paper, we aim to build a video-based model to mitigate the consequences of fall of the elderly at two application scenarios: (1) predict the fall risk caused by unbalanced gait and (2) detect a fall event as soon as it happens. In the first stage, we use a common camera...
The basic necessity of sleep in our life is critically important to ensure our wellbeing. Sufficient sleep of good quality is highly desired in order to have enough energy to live. One of the main factors to measure sleep quality is the amount of body motion during sleep. In our earlier work, we have developed a load cell based system that can detect in-bed body movements and classify them into two...
Various studies have been conducted in the field of the development/deterioration of standing and walking ability. In standing and walking control strategy, the relationship linking visual/somatosensory/vestibular-system information and physical movement is important. Researchers have previously sought to evaluate attitude control based on human sensory information. The authors have also reported...
This paper proposes a monitoring system to prevent falls from a bed. The position of patient on the bed is categorized as stable and unstable. The system has defined the unstable condition as the situation where a patient is lying on the edge of the bed. The patient was then observed using a thermal imagery camera. We extracted x-, and y-axis histograms that can be used as a feature, using this camera...
Every year over 75 000 firefighters are injured and 159 die in the line of duty. Some of these accidents could be averted if first response team leaders had better information about the situation on the ground. The SAFESENS project is developing a novel monitoring system for first responders designed to provide response team leaders with timely and reliable information about their firefighters' status...
Poor sitting postures influence one's health and can cause upper limb and neck disorder. Current solutions for siting posture recognition, however, are impractical due to intrusiveness, high cost or low generalization capability. Particularly, most of the existing solutions are chair-dependent, which are highly coupled with certain types of chairs. In this paper, we design Postureware, a smart cushion,...
This paper proposes a multi-level meta-classifier for identifying human activities based on accelerometer data. The training data consists of 77 subjects performing a combination of 23 different activities and monitored using a single hip-worn triaxial accelerometer. Time and frequency based features were extracted from two-second windows of raw accelerometer data and a subset of the features, together...
The aim of this study is to develop a platform to monitor compliance with brace treatment in patients with scoliosis. Scoliosis is a curvature of the spine that frequently occurs in adolescents. Nonoperative treatment with a thoracolumbosacral orthosis (TLSO) is widely used. However, a brace that is not worn correctly is not effective at controlling scoliosis, regardless of the duration of brace wear...
Continuous field monitoring of load carriage has proven difficult. An algorithm is proposed for estimating load from a single body-worn accelerometer. The accelerometer used is ADXL335. Accelerometer is interfaced with an Arduino Uno. Platform for the algorithm is Arduino Script and MATLAB. The algorithm has three different steps that characterizes torso movement dynamics. The three different steps...
Smartphones are used in the framework of the FARSEEING-InChianti study to gain information on activities of daily living and define objective physical activity profiles. In this study we aimed to investigate the association between mean and extreme values of physical activity and gait characteristics derived from daily living activities and well-established clinical tools. 171 older adults from the...
Despite being considered as simple everyday objects, smartphones have the most innovative sensors and electronics technology built in. These features make them powerful, nonintrusive tools for monitoring the user's physical and cognitive performance. This study aims at exploiting smartphone-based physical activity identification, implementing a classification algorithm that makes use of data extracted...
Smart living and well aging represent key challenges for our society. The precursor state of adverse outcomes that characterize aging has been recognized from scientific community with the frailty syndrome, determined by the loss of physical and psychological capacities. In this paper we define gait and posture indexes that can be effectively and unobtrusively measured using computer vision and RGBD...
Ankle edema an important symptom for monitoring patients with chronic systematic diseases. It is an important indicator of onset or exacerbation of a variety of diseases that disturb cardiovascular, renal, or hepatic system such as heart, liver, and kidney failure, diabetes, etc. The current approaches toward edema assessment are conducted during clinical visits. In-clinic assessments, in addition...
Monitoring group mobility and structure is crucial for public safety management and emergency evacuation. In this paper, we propose a fine-grained mobility classification and structure recognition approach for social groups based on hybrid sensing using mobile devices. First, we present a method which classifies group mobility into four levels, including stationary, strolling, walking and running...
This paper proposes a deep learning classification method for frame-wise recognition of human activities, using raw color (RGB) information. In particular, we present a Convolutional Neural Network (CNN) classification approach for recognising three basic motion activity classes, that cover the vast majority of human activities in the context of a home monitoring environment, namely: sitting, walking...
The joined range-time-frequency representation of ultra-wideband (UWB) Doppler radar signatures from a walking human subject is processed with a state space method (SSM) in which micro-Doppler (m-D) features are extracted for vital sign analysis. To clearly distinguish respiration rates from moving subjects, the SSM, originally developed for radar target identification and sensor fusion, is applied...
This paper proposes a method for human activity classification in home based monitoring. The proposed approach is based on minimum jerk (MinJerk), a primary model for smooth path planning employed by human motor control in upper-extremity motion. Based on new evidences that show common control strategies in lower and upper extremity, MinJerk is adapted in our study to estimate the foot motion with...
Similar to fingerprint and iris pattern, everyone;s gait is unique, and gait has been proposed as a biometric feature for security applications. This paper presents a lightweight accelerometer-based technique for user authentication on smart wearable devices. Designed as an unsupervised classification approach, the proposed authentication technique can learn the user;s gait pattern automatically when...
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