Dina Baga

University of Ioannina

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Co-Authors

Dimitrios I. Fotiadis

University of Ioannina

Spiros Konitsiotis

University of Ioannina

Sofia Tsouli

University of Ioannina

Alexandros T. Tzallas

University of Ioannina

Dimitra A. Chaloglou

George Rigas

University of Ioannina

Markos G. Tsipouras

University of Western Macedonia

Aristidis Likas

University of Ioannina

Evanthia E. Tripoliti

University of Ioannina

Mario Pansera

Universitat Autònoma de Barcelona

Cooperative Institutions

University of Ioannina

University Hospital of Ioannina

Foundation for Research and Technology Hellas

Imperial College London

Universidad Politécnica de Madrid

Center for Research and Technology Thessaly

University of Western Macedonia

Information Technologies Institute

Technological Educational Institute of Epirus

Centre for Research and Technology Hellas

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PERFORM: Building and Mining Electronic Records of Neurological Patients Being Monitored in the Home

IFMBE proceedings (2009)

Reynold Greenlaw María Robledo Juan Estrada Mario Pansera Spiros Konitsiotis

10.1007/978-3-642-03889-1_143

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Citations (9)

PERFORM: A system for the monitoring and management of persons with chronic motor neurodegenerative disorders: A study on Parkinson's Disease and Amyotrophic Lateral Sclerosis

Dina Baga Dimitrios I. Fotiadis Spiros Konitsiotis Metin Akay

In this work we describe a system for the monitoring and management of patients with neurodegenerative diseases, focusing on Parkinson's Disease and Amyotrophic Lateral Sclerosis. The system exploits a single wearable sensors' setting to detect and quantify all patient symptoms. An easy to use touch

Motor symptoms

Disease monitoring

Motor System

10.4108/icst.pervasivehealth2009.5936

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Citations (3)

A decision support tool for optimal Levodopa administration in Parkinson's disease

George Rigas Panagiota Bougia Dina Baga Markos G. Tsipouras Alexandros T. Tzallas

In this work a decision support tool for optimal administration of Levodopa (L-Dopa) in patients with Parkinson's Disease (PD) is presented. The so called Medication Change Proposer (MCP) is part of the PERFORM system, which monitors patient's motion status using a set of wearable sensors, assesses PD symptoms and their severity through dedicated symptoms detection modules (On-Off detection and Levodopa-Induced Dyskinesia detection), and proposes treatment plans to alleviate the symptoms. The methodology is based on the analysis of the outputs of the symptoms detection modules, taking into account the uncertainty (confidence) propagated by their respective classification algorithms. The evaluation of our methodology is performed using artificial follow-up data produced by a specially built simulation environment. The obtained results demonstrate that the MCP outputs compare well with the experts' decisions, indicating high performance.

10.1109/itab.2010.5687798

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Citations (8)

Using partial decision trees to predict Parkinson’s symptoms: A new approach for diagnosis and therapy in patients suffering from Parkinson’s disease

Computers in Biology and Medicine (2011)

Themis P. Exarchos Alexandros T. Tzallas Dina Baga Dimitra A. Chaloglou Dimitrios I. Fotiadis

Association (psychology)

10.1016/j.compbiomed.2011.11.008

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Citations (33)

AN AUTOMATED METHOD FOR THE MONITORING AND EVALUATION OF LONG BONES FRACTURE HEALING

Vasilios C. Protopappas Dina Baga Dimitrios I. Fotiadis Aristidis Likas

10.1142/9789812777140_0034

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Citations (0)

Assessment of Tremor Activity in the Parkinson’s Disease Using a Set of Wearable Sensors

IEEE Transactions on Information Technology in Biomedicine (2012)

George Rigas Alexandros T. Tzallas Markos G. Tsipouras Panagiota Bougia Evanthia E. Tripoliti

Tremor is the most common motor disorder of Parkinson's disease (PD) and consequently its detection plays a crucial role in the management and treatment of PD patients. The current diagnosis procedure is based on subject-dependent clinical assessment, which has a difficulty in capturing subtle tremor features. In this paper, an automated method for both resting and action/postural tremor assessment is proposed using a set of accelerometers mounted on different patient's body segments. The estimation of tremor type (resting/action postural) and severity is based on features extracted from the acquired signals and hidden Markov models. The method is evaluated using data collected from 23 subjects (18 PD patients and 5 control subjects). The obtained results verified that the proposed method successfully: 1) quantifies tremor severity with 87 % accuracy, 2) discriminates resting from postural tremor, and 3) discriminates tremor from other Parkinsonian motor symptoms during daily activities.

Resting tremor

10.1109/titb.2011.2182616

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Citations (225)

An Ultrasound Wearable System for the Monitoring and Acceleration of Fracture Healing in Long Bones

IEEE Transactions on Biomedical Engineering (2005)

Vasilios C. Protopappas Dina Baga Dimitrios I. Fotiadis Aristidis Likas A. Papachristos

An ultrasound wearable system for remote monitoring and acceleration of the healing process in fractured long bones is presented. The so-called USBone system consists of a pair of ultrasound transducers, implanted into the fracture region, a wearable device and a centralized unit. The wearable device is responsible to carry out ultrasound measurements using the axial-transmission technique and initiate therapy sessions of low-intensity pulsed ultrasound. The acquired measurements and other data are wirelessly transferred from the patient-site to the centralized unit, which is located in a clinical setting. The evaluation of the system on an animal tibial osteotomy model is also presented. A dataset was constructed for monitoring purposes consisting of serial ultrasound measurements, follow-up radiographs, quantitative computed tomography-based densitometry and biomechanical data. The animal study demonstrated the ability of the system to collect ultrasound measurements in an effective and reliable fashion and participating orthopaedic surgeons accepted the system for future clinical application. Analysis of the acquired measurements showed that the pattern of evolution of the ultrasound velocity through healing bones over the postoperative period monitors a dynamic healing process. Furthermore, the ultrasound velocity of radiographically healed bones returns to 80% of the intact bone value, whereas the correlation coefficient of the velocity with the material and mechanical properties of the healing bone ranges from 0.699 to 0.814. The USBone system constitutes the first telemedicine system for the out-hospital management of patients sustained open fractures and treated with external fixation devices.

10.1109/tbme.2005.851507

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Citations (97)

PERFORM: A platform for monitoring and management of chronic neurodegenerative diseases: The Parkinson and Amyotrophic Lateral Sclerosis case

Dina Baga Dimitrios I. Fotiadis Spiros Konitsiotis Sofia Tsouli Maria Diakou

In this work we present a system for the monitoring and management of neurodegenerative diseases, such as the Parkinson's Disease (PD) and amyotrophic lateral sclerosis (ALS). The purpose of the system is to monitor patient's motor symptoms, and assist the clinician in the evaluation of both the current patient status and the disease progression. The system progresses one step further and suggests appropriate patient treatment changes, based on previously stored or accumulated medical knowledge. In this work, we focus on the description of the wearable platforms used to monitor the patient motor status at the patient's environment.

Motor symptoms

Disease monitoring

10.1109/ner.2009.5109220

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Citations (9)

PERFORM: First steps in the assessment of patient motion status and support to treatment changes

George Rigas Alexandros T. Tzallas Dina Baga Themis P. Exarchos Christos D. Katsis

In the current work, a system for the monitoring, assessment and management of patients with chronic movement disorders such as Parkinson's disease (PD) is presented. The so called PERFORM system consists of the patient and the healthcare center subsystem. PERFORM monitors patient's motion status in daily activities, using a set of light wearable sensors. Based on the analysis of the acquired signals, PERFORM assesses PD symptoms and their severity, integrates patient's demographic, clinical and history data and proposes treatment plans based on advanced data mining algorithms. In this work we present two main modules of PERFORM system, the tremor assessment module and the data miner module.

Remote patient monitoring

Motion Capture

10.1109/itab.2009.5394349

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Citations (0)