The implementation of advanced driver assistance systems (ADAS) has significantly impacted the prevention of traffic accidents, particularly through the forward collision warning (FCW) algorithm. Nevertheless, traffic conflicts on traffic routes remain a significant issue, since most FCW algorithms cannot accurately determine the distance between the host vehicle (HV) and remote vehicle (RV) on curved roads. Hence, this study proposes a vector-based FCW (V-FCW) algorithm to address the issue of false warnings on unconventional road sections.
View Article and Find Full Text PDFThe monitoring of treadmill walking energy expenditure (EE) plays an important role in health evaluations and management, particularly in older individuals and those with chronic diseases. However, universal and highly accurate prediction methods for walking EE are still lacking. In this paper, we propose an ensemble neural network (ENN) model that predicts the treadmill walking EE of younger and older adults and stroke survivors with high precision based on easy-to-obtain features.
View Article and Find Full Text PDFMagnetic soft robots (MSRs) can achieve controllable shape-morphing by magnetic programming to the magnetic elastomer. However, the magnetization profile is usually implemented on a continuous region and is unchangeable. The deformation and function design of MSR hence is limited.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
April 2021
Neurologists judge the severity of Parkinsonian motor symptoms according to clinical scales, and their judgments exist inconsistent because of differences in clinical experience. Correspondingly, inertial sensing-based wearable devices (ISWDs) produce objective and standardized quantifications. However, ISWDs indirectly quantify symptoms by parametric modeling of angular velocities and linear accelerations nd trained by the judgments of several neurologists through supervised learning algorithms.
View Article and Find Full Text PDFSheng Wu Yi Xue Gong Cheng Xue Za Zhi
June 2018
At present the parkinsonian rigidity assessment depends on subjective judgment of neurologists according to their experience. This study presents a parkinsonian rigidity quantification system based on the electromechanical driving device and mechanical impedance measurement method. The quantification system applies the electromechanical driving device to perform the rigidity clinical assessment tasks (flexion-extension movements) in Parkinson's disease (PD) patients, which captures their motion and biomechanical information synchronously.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2017
Bradykinesia is one of the primary characteristic symptoms of Parkinson's disease (PD). Ten-second whole-hand-grasps action was chosen to assess bradykinesia severity in this study. A quantification assessment system based on a self-developed wearable device was proposed to assess the severity of the parkinsonian bradykinesia.
View Article and Find Full Text PDFThe objective of this study was to explore the feasibility of using wearable devices to quantitatively measure the daily activity in patients with Parkinson's disease (PD) and to monitor medication-induced motor fluctuations. In this case-controlled study, we used monitored daily movement function in 21 patients with Parkinson's disease and 20 healthy volunteers. We analyzed the exercise types and sleep duration in the two groups and evaluated the correlation between daily movement function and age, gender, education, disease duration, Hohn-Yahr stage, UPDRS-II score, UPDRS-III score, and levodopa dose.
View Article and Find Full Text PDFMed Devices (Auckl)
February 2016
Wireless capsule endoscope achieved great success, however, the maneuvering of wireless capsule endoscope is challenging at present. A magnetic driving instrument, including two bar magnets, a stepper motor, a motor driver, a motor controller, and a power supplier, was developed to generate rotational magnetic fields. Permanent magnet ring, magnetized as S and N poles radially and mounted spiral structure on the surface, acted as a capsule.
View Article and Find Full Text PDFSensors (Basel)
September 2015
Quantitative assessment of parkinsonian tremor based on inertial sensors can provide reliable feedback on the effect of medication. In this regard, the features of parkinsonian tremor and its unique properties such as motor fluctuations and dyskinesia are taken into account. Least-square-estimation models are used to assess the severities of rest, postural, and action tremors.
View Article and Find Full Text PDFBackground: As the most characteristic feature of Parkinson's disease (PD), bradykinesia (slowness of movement) affects all patients with Parkinson's disease and interferes with their daily activities. This study introduces a wearable bradykinesia assessment system whose core component is composed of an inertial measurement unit.
Methods: The system diagram and assessment task were defined in accordance with clinical requirements from neurologists.
Annu Int Conf IEEE Eng Med Biol Soc
September 2015
Rigidity is one of the primary symptoms of Parkinson's disease. Passive flexion and extension of the elbow is used to assess rigidity in this study. An examiner flexes and extends the subject's elbow joint through a rigidity assessment cuff attached around the wrist.
View Article and Find Full Text PDFBiomed Eng Online
February 2012
Continuous Positive Airway Pressure (CPAP) ventilation remains a mainstay treatment for obstructive sleep apnea syndrome (OSAS). Good pressure stability and pressure reduction during exhalation are of major importance to ensure clinical efficacy and comfort of CPAP therapy. In this study an experimental CPAP ventilator was constructed using an application-specific CPAP blower/motor assembly and a microprocessor.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
April 2009
In this paper, we propose a novel localization algorithm for tracking a magnet inside the capsule endoscope by 3-axis magnetic sensors array. In the algorithm, we first use an improved linear algorithm to obtain the localization parameters by finding the eigenvector corresponding to the minimum eigenvalue of the objective matrix. These parameters are used as the initial guess of the localization parameters in the nonlinear localization algorithm, and the nonlinear algorithm searches for more appropriate parameters that can minimize the objective error function.
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