A new software to detect and measure the gait with a smartphone in the sock
ESSKA Academy. Conteduca F. 11/08/19; 284392; epEKA-62 Topic: Biomechanics
Fabio Conteduca
Fabio Conteduca
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A new software to detect and measure the gait with a smartphone in the sock

ePoster - epEKA-62

Topic: TKA

Conteduca F.1, Drogo P.1, Andreozzi V.1, Caperna L.1, Conteduca R.2, Ferretti A.1
1La Sapienza University of Rome, Sant Andrea Hospital, Rome, Italy, 2Rome Luiss University, Rome, Italy

Introduction: Currently, the use of Inertial Measurement Unit(IMU) is a common method for the assessment of body movements in a daily life setting. IMU is a device that combines accelerometers, gyroscopes and magnetometers. Currently, the market offers smartphone having IMU technologies inside . It is, therefore, possible to design specific applications for this goal.
In this study, we propose to develop a novel smartphone-based movement assessment protocol (StepHolter) for the evaluation of lower limb kinematics.
We validate the software comparing movements with the gold standard system Motion Analysis System (Elite, BTS Inc., Milano, Italy).
Methods: StepHolter was tested in a sample of healthy subjects using a Motion Analysis System (Elite, BTS Inc., Milano, Italy). We analyzed two specific motor task: walking and climb stairs. Each subject walked for ten meters and climbed five steps, each subject repeated the task five times and the average values were calculated. The smartphone was attached with a strap at the medial side of the tibia with the top of the telephone at the level of the Joint Line. The procedure starts with calibration that defines the three planes where the movement takes place. After the calibration, the subject starts the two defined tasks.
We recorded data from Motion Analysis System and the smartphone
Results: The results between the smartphone and the motion analysis system were compared.
Kinematic data were provided by both methods using Spearman 's correlation.
The intra-class correlation coefficient (ICC) with 95 % confidence interval to evaluate the degree of consistency among measurements was confirmed.
Software possibilities
After the test is made the smartphone can store and transmit the data to a specific web page by a QR code. Gait movement can be reproduced and data can be retrieved in an excel format to easily plan a research study.
Conclusions: StepHolter software and a smartphone can easily detect kinematics of the leg like the professional Motion Analysis System avoiding big expenses for a professional machine inside a specifically closed ambient.
Moreover, StepHolter offers the possibility to study the gait analysis everywhere during daily life activity.
A new software to detect and measure the gait with a smartphone in the sock

ePoster - epEKA-62

Topic: TKA

Conteduca F.1, Drogo P.1, Andreozzi V.1, Caperna L.1, Conteduca R.2, Ferretti A.1
1La Sapienza University of Rome, Sant Andrea Hospital, Rome, Italy, 2Rome Luiss University, Rome, Italy

Introduction: Currently, the use of Inertial Measurement Unit(IMU) is a common method for the assessment of body movements in a daily life setting. IMU is a device that combines accelerometers, gyroscopes and magnetometers. Currently, the market offers smartphone having IMU technologies inside . It is, therefore, possible to design specific applications for this goal.
In this study, we propose to develop a novel smartphone-based movement assessment protocol (StepHolter) for the evaluation of lower limb kinematics.
We validate the software comparing movements with the gold standard system Motion Analysis System (Elite, BTS Inc., Milano, Italy).
Methods: StepHolter was tested in a sample of healthy subjects using a Motion Analysis System (Elite, BTS Inc., Milano, Italy). We analyzed two specific motor task: walking and climb stairs. Each subject walked for ten meters and climbed five steps, each subject repeated the task five times and the average values were calculated. The smartphone was attached with a strap at the medial side of the tibia with the top of the telephone at the level of the Joint Line. The procedure starts with calibration that defines the three planes where the movement takes place. After the calibration, the subject starts the two defined tasks.
We recorded data from Motion Analysis System and the smartphone
Results: The results between the smartphone and the motion analysis system were compared.
Kinematic data were provided by both methods using Spearman 's correlation.
The intra-class correlation coefficient (ICC) with 95 % confidence interval to evaluate the degree of consistency among measurements was confirmed.
Software possibilities
After the test is made the smartphone can store and transmit the data to a specific web page by a QR code. Gait movement can be reproduced and data can be retrieved in an excel format to easily plan a research study.
Conclusions: StepHolter software and a smartphone can easily detect kinematics of the leg like the professional Motion Analysis System avoiding big expenses for a professional machine inside a specifically closed ambient.
Moreover, StepHolter offers the possibility to study the gait analysis everywhere during daily life activity.
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