AIMC Topic: Feasibility Studies

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Compensating Hand Function in Chronic Stroke Patients Through the Robotic Sixth Finger.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
A novel solution to compensate hand grasping abilities is proposed for chronic stroke patients. The goal is to provide the patients with a wearable robotic extra-finger that can be worn on the paretic forearm by means of an elastic band. The proposed...

Effects on mobility training and de-adaptations in subjects with Spinal Cord Injury due to a Wearable Robot: a preliminary report.

BMC neurology
BACKGROUND: Spinal cord injury (SCI) is a severe neurological disorder associated not only with ongoing medical complications but also with a significant loss of mobility and participation. The introduction of robotic technologies to recover lower li...

Design and Evaluation of a Soft and Wearable Robotic Glove for Hand Rehabilitation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In the modern world, due to an increased aging population, hand disability is becoming increasingly common. The prevalence of conditions such as stroke is placing an ever-growing burden on the limited fiscal resources of health care providers and the...

Feasibility of Active Machine Learning for Multiclass Compound Classification.

Journal of chemical information and modeling
A common task in the hit-to-lead process is classifying sets of compounds into multiple, usually structural classes, which build the groundwork for subsequent SAR studies. Machine learning techniques can be used to automate this process by learning c...

Decoding intracranial EEG data with multiple kernel learning method.

Journal of neuroscience methods
BACKGROUND: Machine learning models have been successfully applied to neuroimaging data to make predictions about behavioral and cognitive states of interest. While these multivariate methods have greatly advanced the field of neuroimaging, their app...

Methodological considerations for using umu assay to assess photo-genotoxicity of engineered nanoparticles.

Mutation research. Genetic toxicology and environmental mutagenesis
In this study we investigated the feasibility of high-throughput (96-well plate) umu assay to test the genotoxic effect of TiO2 engineered nanoparticles (ENPs) under UV light (full spectrum) and visible light (455 nm). Exposure of TiO2 ENPs to up to ...

Submaximal cardiopulmonary thresholds on a robotics-assisted tilt table, a cycle and a treadmill: a comparative analysis.

Biomedical engineering online
BACKGROUND: The robotics-assisted tilt table (RATT), including actuators for tilting and cyclical leg movement, is used for rehabilitation of severely disabled neurological patients. Following further engineering development of the system, i.e. the a...

Predicting High Imaging Utilization Based on Initial Radiology Reports: A Feasibility Study of Machine Learning.

Academic radiology
RATIONALE AND OBJECTIVES: Imaging utilization has significantly increased over the last two decades, and is only recently showing signs of moderating. To help healthcare providers identify patients at risk for high imaging utilization, we developed a...

Feasibility study into self-administered training at home using an arm and hand device with motivational gaming environment in chronic stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Assistive and robotic training devices are increasingly used for rehabilitation of the hemiparetic arm after stroke, although applications for the wrist and hand are trailing behind. Furthermore, applying a training device in domestic set...

Using Wearable Sensors and Machine Learning Models to Separate Functional Upper Extremity Use From Walking-Associated Arm Movements.

Archives of physical medicine and rehabilitation
OBJECTIVE: To improve measurement of upper extremity (UE) use in the community by evaluating the feasibility of using body-worn sensor data and machine learning models to distinguish productive prehensile and bimanual UE activity use from extraneous ...