Faller classification in elderly populations can facilitate preventative care before a fall occurs. A novel wearable-sensor based faller classification method for the elderly was developed using accelerometer-based features from straight walking and...
Activity recognition using wearable sensors has become essential for a variety of applications. Tri-axial accelerometers are the most widely used sensor for activity recognition. Although various features have been used to capture patterns and classi...
Bearings are not only the most important element but also a common source of failures in rotary machinery. Bearing fault prognosis technology has been receiving more and more attention recently, in particular because it plays an increasingly importan...
The continuing advancements in technology have resulted in an explosion in the use of interconnected devices and sensors. Internet-of-Things (IoT) systems are used to provide remote solutions in different domains, like healthcare and security. A comm...
Accelerometer sensors and artificial intelligence (AI) are reshaping automated behavior monitoring in precision livestock management, yet their joint deployment on extensive rangelands is constrained by energy and bandwidth budgets. Low-Power Long-Ra...
With the increasing popularity of smartphones, user identification has become a critical component to ensure security and privacy. This study looked into how smartphone sensors’ data can be utilized to identify/authenticate users and gives sugg...
Since surface electromyograghic (sEMG) signals are non-invasive and capable of reflecting humans’ motion intention, they have been widely used for the motion recognition of upper limbs. However, limited research has been conducted for lower limbs, be...
Hemiplegia affects a significant portion of the human population. It is a condition that causes motor impairment and severely reduces the patient’s quality of life. This paper presents an automatic system for identifying the hemiplegia type (ri...
Accelerometers have been widely embedded in most current mobile devices, enabling easy and intuitive operations. This paper proposes a Motion Gesture Recognition system (MGRA) based on accelerometer data only, which is entirely implemented on mobile...
Gait analysis is commonly used to detect foot disorders and abnormalities such as supination, pronation, unstable left foot and unstable right foot. Early detection of these abnormalities could help us to correct the walking posture and avoid getting...
Estimation of temporospatial clinical features of gait (CFs), such as step count and length, step duration, step frequency, gait speed, and distance traveled, is an important component of community-based mobility evaluation using wearable acceleromet...
Although wearable accelerometers can successfully recognize activities and detect falls, their adoption in real life is low because users do not want to wear additional devices. A possible solution is an accelerometer inside a wrist device/smartwatch...
Given the ubiquity of mobile devices, understanding the context of human activity with non-intrusive solutions is of great value. A novel deep neural network model is proposed, which combines feature extraction and convolutional layers, able to recog...
A user of a smartphone may feel convenient, happy, safe, etc., if his/her smartphone works smartly based on his/her context or the context of the device. In this article, we deal with the position of a smartphone on the body and carrying items like b...
Human activity recognition (HAR) techniques are playing a significant role in monitoring the daily activities of human life such as elderly care, investigation activities, healthcare, sports, and smart homes. Smartphones incorporated with varieties o...
Advances in medical care has reduced the rate of mortality from strokes, but the incidence of stroke has remained stable while the incidence of ministrokes has increased. Most stroke victims require long-term care, imposing a heavy financial and emot...
Carotid artery disease, including atherosclerotic stenosis and non-atherosclerotic abnormalities, substantially increases ischemic stroke risk and motivates accessible tools for early screening. Current diagnostic pathways rely on clinic-based imagin...
This paper focuses on the development and validation of an automatic learning system for the classification of tactile data in form of vibro-tactile (accelerometer) and audio (microphone) data for texture recognition. A novel combination of features...
Differences in gait patterns of children with Duchenne muscular dystrophy (DMD) and typically developing (TD) peers are visible to the eye, but quantifications of those differences outside of the gait laboratory have been elusive. In this work, we me...
Terrain classification provides valuable information for both control and navigation algorithms of wheeled mobile robots. In this paper, a novel online outdoor terrain classification algorithm is proposed for wheeled mobile robots. The algorithm is b...
Hemiplegia is a condition caused by brain injury and affects a significant percentage of the population. The effect of patients suffering from this condition is a varying degree of weakness, spasticity, and motor impairment to the left or right side...
This paper proposes a method for monitoring driver safety levels using a data fusion approach based on several discrete data types: eye features, bio-signal variation, in-vehicle temperature, and vehicle speed. The driver safety monitoring system was...
Smartphone-based activity recognition (SP-AR) recognizes users’ activities using the embedded accelerometer sensor. Only a small number of previous works can be classified as online systems, i.e., the whole process (pre-processing, feature extraction...
During the in-hospital optimization of dopaminergic dosage for Parkinson’s disease, drug-induced dyskinesias emerge as a common side effect. Wrist-worn devices present a substantial opportunity for continuous movement recording and the supporti...
Advancements in wearable sensors technologies provide prominent effects in the daily life activities of humans. These wearable sensors are gaining more awareness in healthcare for the elderly to ensure their independent living and to improve their co...
Human Activity Recognition (HAR) using embedded sensors in smartphones and smartwatch has gained popularity in extensive applications in health care monitoring of elderly people, security purpose, robotics, monitoring employees in the industry, and o...
This paper presents a detailed analysis of signal data acquired from wearable sensors such as accelerometers and barometric altimeters for human activity recognition, with an emphasis on fall detection. This research addressed two types of activity r...
Falls by the elderly pose considerable health hazards, leading not only to physical harm but a number of other related problems. A timely alert about a deteriorating gait, as an indication of an impending fall, can assist in fall prevention. In this...
Even though practicing sports has great health benefits, it also entails a risk of developing overuse injuries, which can elicit a negative impact on physical, mental, and financial health. Being able to predict the risk of an overuse injury arising...
One of the most common symptoms observed among most of the Parkinson’s disease patients that affects movement pattern and is also related to the risk of fall, is usually termed as “freezing of gait (FoG)”. To allow systematic assess...
This paper aims to assess the use of Inertial Measurement Unit (IMU) sensors to identify gait asymmetry by extracting automatic gait features. We design and develop an android app to collect real time synchronous IMU data from legs. The results from...
In this paper, a methodology is described aiming at emphasizing physical and metrological criteria in feature selection for condition monitoring of a real scale mechatronic system. The device is used for packaging applications according to the moveme...
We extract the informative features of gyroscope signals using the discrete wavelet transform (DWT) decomposition and provide them as input to multi-layer feed-forward artificial neural networks (ANNs) for leg motion classification. Since the DWT is...
With the growing number of people seeking medical advice due to low back pain (LBP), individualised physiotherapeutic rehabilitation is becoming increasingly relevant. Thirty volunteers were asked to perform three typical LBP rehabilitation exercises...
Wearable sensors have become increasingly popular for assessing athletic performance, but the optimal methods for processing and analyzing the data remain unclear. This study investigates the efficacy of discrete and continuous feature-extraction met...
Due to the increasing age of the European population, there is a growing interest in performing research that will aid in the timely and unobtrusive detection of emerging diseases. For such tasks, mobile devices have several sensors, facilitating the...
Smartphone location recognition aims to identify the location of a smartphone on a user in specific actions such as talking or texting. This task is critical for accurate indoor navigation using pedestrian dead reckoning. Usually, for that task, a su...
This study aims to build a system for detecting a driver’s internal state using body-worn sensors. Our system is intended to detect inattentive driving that occurs during long-term driving on a monotonous road, such as a high-way road. The inat...
The main errors of MEMS accelerometers are misalignments of their sensitivity axes, thermal and long-term drifts, imprecise factory calibration, and aging phenomena. In order to reduce these errors, a two-axial tilt sensor comprising a triaxial MEMS...
The treatment of mood disorders, which can become a lifelong process, varies widely in efficacy between individuals. Most options to monitor mood rely on subjective self-reports and clinical visits, which can be burdensome and may not portray an accu...
This paper introduces a two-stage approach to the detection of people eating and/or drinking for the purposes of surveillance of daily life. With the sole use of wearable accelerometer sensor attached to somebody’s (man or a woman) wrists, this two-s...
A set of commercial triaxial micro-electromechanical systems (MEMS) accelerometers was calibrated using a custom-designed test bench featuring a rotating table. The calibration setup enabled simultaneous assessment of all accelerometer measurement co...
Hip-worn triaxial accelerometers are widely used to assess physical activity in terms of energy expenditure. Methods for classification in terms of different types of activity of relevance to the skeleton in populations at risk of osteoporosis are no...
The use of digital accelerometers featuring high sensitivity and low noise levels in wireless smart sensors (WSSs) is becoming increasingly common for structural health monitoring (SHM) applications. Improvements in the design of Micro Electro-Mechan...
Recent developments in smartphones have increased the processing capabilities and equipped these devices with a number of built-in multimodal sensors, including accelerometers, gyroscopes, GPS interfaces, Wi-Fi access, and proximity sensors. Despite...
The use of accelerometer signals for early recognition of severe slugging is investigated in a pipeline-riser system conveying an air–water two-phase flow, where six accelerometers are installed from the bottom to the top of the riser. Twelve d...
A novel high-precision vacuum microelectronic accelerometer has been successfully fabricated and tested in our laboratory. This accelerometer has unique advantages of high sensitivity, fast response, and anti-radiation stability. It is a prototype in...
Consumer-grade sleep trackers represent a promising tool for large scale studies and health management. However, the potential and limitations of these devices remain less well quantified. Addressing this issue, we aim at providing a comprehensive an...
Background: Human activity recognition (HAR) plays a pivotal role in digital healthcare, enabling applications such as exercise monitoring and elderly care. However, traditional HAR methods relying on accelerometer data often require complex preproce...
Structural health monitoring (SHM) is playing an increasingly important role in ensuring the safety of structures. A shift of SHM research away from traditional wired methods toward the use of wireless smart sensors (WSS) has been motivated by the at...
of 13