A Hybrid Approach for Recognizing ADLs and Care Activities Using Inertial Sensors and RFID

2009 ◽  
pp. 178-188 ◽  
Author(s):  
Albert Hein ◽  
Thomas Kirste
Keyword(s):  
Inertial Sensors ◽  
Hybrid Approach

Human Motion Capture with Sparse Inertial Sensors and Video

2020 ◽  
Author(s):  
Timo von Marcard
Keyword(s):  
Global Optimization ◽  
Optimization Problem ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Hybrid Approach ◽  
Human Motion ◽  
The Body ◽  
Sensor Data ◽  
Discrete Optimization Problem ◽  
Global Optimization Problem

This thesis explores approaches to capture human motions with a small number of sensors. In the first part of this thesis an approach is presented that reconstructs the body pose from only six inertial sensors. Instead of relying on pre-recorded motion databases, a global optimization problem is solved to maximize the consistency of measurements and model over an entire recording sequence. The second part of this thesis deals with a hybrid approach to fuse visual information from a single hand-held camera with inertial sensor data. First, a discrete optimization problem is solved to automatically associate people detections in the video with inertial sensor data. Then, a global optimization problem is formulated to combine visual and inertial information. The propose  approach enables capturing of multiple interacting people and works even if many more people are visible in the camera image. In addition, systematic inertial sensor errors can be compensated, leading to a substantial in...

Surgical and endovascular hybrid approach in peripheral arterial disease of the lower limbs

VASA ◽  
2016 ◽  
Vol 45 (5) ◽  
pp. 417-422 ◽  
Author(s):  
Anouk Grandjean ◽  
Katia Iglesias ◽  
Céline Dubuis ◽  
Sébastien Déglise ◽  
Jean-Marc Corpataux ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Peripheral Arterial Disease ◽  
Limb Salvage ◽  
Hybrid Approach ◽  
Arterial Disease ◽  
Early Mortality ◽  
Secondary Patency ◽  
Limb Salvage Rate ◽  
Peripheral Arterial ◽  
Salvage Rate

Abstract. Background: Multilevel peripheral arterial disease is frequently observed in patients with intermittent claudication or critical limb ischemia. This report evaluates the efficacy of one-stage hybrid revascularization in patients with multilevel arterial peripheral disease. Patients and methods: A retrospective analysis of a prospective database included all consecutive patients treated by a hybrid approach for a multilevel arterial peripheral disease. The primary outcome was the patency rate at 6 months and 1 year. Secondary outcomes were early and midterm complication rate, limb salvage and mortality rate. Statistical analysis, including a Kaplan-Meier estimate and univariate and multivariate Cox regression analyses were carried out with the primary, primary assisted and secondary patency, comparing the impact of various risk factors in pre- and post-operative treatments. Results: 64 patients were included in the study, with a mean follow-up time of 428 days (range: 4 − 1140). The technical success rate was 100 %. The primary, primary assisted and secondary patency rates at 1 year were 39 %, 66 % and 81 %, respectively. The limb-salvage rate was 94 %. The early mortality rate was 3.1 %. Early and midterm complication rates were 15.4 % and 6.4 %, respectively. The early mortality rate was 3.1 %. Conclusions: The hybrid approach is a major alternative in the treatment of peripheral arterial disease in multilevel disease and comorbid patients, with low complication and mortality rates and a high limb-salvage rate.

Delayed Closure of Multiple Muscular Ventricular Septal Defects in an Infant after Coarctation Repair and a Hybrid Procedure�A Case Report

2011 ◽  
Vol 14 (1) ◽  
pp. 67 ◽  
Author(s):  
Ireneusz Haponiuk ◽  
Maciej Chojnicki ◽  
Radosaw Jaworski ◽  
Jacek Juciski ◽  
Mariusz Steffek ◽  
...  
Keyword(s):  
Septal Defect ◽  
Color Doppler ◽  
Hybrid Approach ◽  
Ventricular Septal Defects ◽  
Color Doppler Echocardiography ◽  
Septal Defects ◽  
Coarctation Repair ◽  
Step Procedure ◽  
The Right ◽  
Delayed Closure

There are several strategies of surgical approach for the repair of multiple muscular ventricular septal defects (mVSDs), but none leads to a fully predictable, satisfactory therapeutic outcome in infants. We followed a concept of treating multiple mVSDs consisting of a hybrid approach based on intraoperative perventricular implantation of occluding devices. In this report, we describe a 2-step procedure consisting of a final hybrid approach for multiple mVSDs in the infant following initial coarctation repair with pulmonary artery banding in the newborn. At 7 months, sternotomy and debanding were performed, the right ventricle was punctured under transesophageal echocardiographic guidance, and the 8-mm device was implanted into the septal defect. Color Doppler echocardiography results showed complete closure of all VSDs by 11 months after surgery, probably via a mechanism of a localized inflammatory response reaction, ventricular septum growth, and implant endothelization.

Deadlift Recognition and Application based on Multiple Modalities using Recurrent Neural Network

2020 ◽  
Vol 2020 (17) ◽  
pp. 2-1-2-6
Author(s):  
Shih-Wei Sun ◽  
Ting-Chen Mou ◽  
Pao-Chi Chang
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Network Structure ◽  
Inertial Sensors ◽  
Body Movement ◽  
The Body ◽  
Body Parts ◽  
Multimodal Sensing ◽  
Multiple Devices ◽  
Neural Network Structure

To improve the workout efficiency and to provide the body movement suggestions to users in a “smart gym” environment, we propose to use a depth camera for capturing a user’s body parts and mount multiple inertial sensors on the body parts of a user to generate deadlift behavior models generated by a recurrent neural network structure. The contribution of this paper is trifold: 1) The multimodal sensing signals obtained from multiple devices are fused for generating the deadlift behavior classifiers, 2) the recurrent neural network structure can analyze the information from the synchronized skeletal and inertial sensing data, and 3) a Vaplab dataset is generated for evaluating the deadlift behaviors recognizing capability in the proposed method.

A Hybrid Approach for Virtual Machine Migration in Cloud Computing Environment

2017 ◽  
Vol 7 (9) ◽  
pp. 30 ◽  
Author(s):  
Ramandeep Kaur
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Heuristic Algorithms ◽  
Hybrid Approach ◽  
Cloud Infrastructure ◽  
Virtual Machine Migration ◽  
Bee Colony ◽  
Effective Manner ◽  
Effective Performance

A lot of research has been done in the field of cloud computing in computing domain.  For its effective performance, variety of algorithms has been proposed. The role of virtualization is significant and its performance is dependent on VM Migration and allocation. More of the energy is absorbed in cloud; therefore, the utilization of numerous algorithms is required for saving energy and efficiency enhancement in the proposed work. In the proposed work, green algorithm has been considered with meta heuristic algorithms, ABC (Artificial Bee colony .Every server has to perform different or same functions. A cloud computing infrastructure can be modelled as Primary Machineas a set of physical Servers/host PM1, PM2, PM3… PMn. The resources of cloud infrastructure can be used by the virtualization technology, which allows one to create several VMs on a physical server or host and therefore, lessens the hardware amount and enhances the resource utilization. The computing resource/node in cloud is used through the virtual machine. To address this problem, data centre resources have to be managed in resource -effective manner for driving Green Cloud computing that has been proposed in this work using Virtual machine concept with ABC and Neural Network optimization algorithm. The simulations have been carried out in CLOUDSIM environment and the parameters like SLA violations, Energy consumption and VM migrations along with their comparison with existing techniques will be performed.

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