scholarly journals A Framework for Sensor-Based Assessment of Upper-Limb Functioning in Hemiparesis

2021 ◽  
Vol 15 ◽  
Author(s):  
Ann David ◽  
Tanya Subash ◽  
S. K. M. Varadhan ◽  
Alejandro Melendez-Calderon ◽  
Sivakumar Balasubramanian
Keyword(s):  
Upper Limb ◽  
Daily Life ◽  
Wearable Sensors ◽  
Clinical Work ◽  
Behavioral Pattern ◽  
Inertial Measurement Units ◽  
Compensatory Strategies ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Using Data

The ultimate goal of any upper-limb neurorehabilitation procedure is to improve upper-limb functioning in daily life. While clinic-based assessments provide an assessment of what a patient can do, they do not completely reflect what a patient does in his/her daily life. The use of compensatory strategies such as the use of the less affected upper-limb or excessive use of trunk in daily life is a common behavioral pattern seen in patients with hemiparesis. To this end, there has been an increasing interest in the use of wearable sensors to objectively assess upper-limb functioning. This paper presents a framework for assessing upper-limb functioning using sensors by providing: (a) a set of definitions of important constructs associated with upper-limb functioning; (b) different visualization methods for evaluating upper-limb functioning; and (c) two new measures for quantifying how much an upper-limb is used and the relative bias in their use. The demonstration of some of these components is presented using data collected from inertial measurement units from a previous study. The proposed framework can help guide the future technical and clinical work in this area to realize valid, objective, and robust tools for assessing upper-limb functioning. This will in turn drive the refinement and standardization of the assessment of upper-limb functioning.

scholarly journals A Framework for Sensor-based Assessment of Upper-limb Functioning

2021 ◽  
Author(s):  
Ann David ◽  
Tanya Subash ◽  
SKM Varadhan ◽  
Alejandro Melendez-Calderon ◽  
Sivakumar Balasubramanian
Keyword(s):  
Upper Limb ◽  
Daily Life ◽  
Wearable Sensors ◽  
Clinical Work ◽  
Behavioral Pattern ◽  
Upper Limbs ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Using Data

AbstractThe ultimate goal of any upper-limb neurorehabilitation procedure is to improve upper-limb functioning in daily life. While clinic-based assessments provide an assessment of what a patient can do, they do not completely reflect what a patient does in his/her daily life. The compensatory use of the less affected upper-limb (e.g. “learned non-use”) in daily life is a common behavioral pattern seen in patients with hemiparesis. To this end, there has been an increasing interest in the use of wearable sensors to objectively assess upper-limb functioning. This paper presents a framework for assessing upper-limb functioning using sensors by providing: (a) a set of definitions of important construct associated with upper-limb functioning; (b) presenting different visualization methods for evaluating upper-limb functioning, along ways to qualitatively analyze different visualization methods; and (c) two new measures for quantifying how much an upper-limb is used and the relative bias in the use of the two upper-limbs. The demonstration of some of these components is presented using data collected from inertial measurement units from a previous study. The proposed framework can help guide the future technical and clinical work in this area to realize a valid, objective, and robust tool for assessing upper-limb functioning. This will in turn drive the refinement and standardization of the assessment of upper-limb functioning.

scholarly journals Continuous Authentication of Automotive Vehicles Using Inertial Measurement Units

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5283 ◽  
Author(s):  
Gianmarco Baldini ◽  
Filip Geib ◽  
Raimondo Giuliani
Keyword(s):  
Wearable Sensors ◽  
Measurement Unit ◽  
Daily Routine ◽  
Inertial Measurement Units ◽  
Digital Output ◽  
Inertial Measurement ◽  
Continuous Authentication ◽  
Measurement Units ◽  
Analytical Approaches ◽  
Road Segments

The concept of Continuous Authentication is to authenticate an entity on the basis of a digital output generated in a continuous way by the entity itself. This concept has recently been applied in the literature for the continuous authentication of persons on the basis of intrinsic features extracted from the analysis of the digital output generated by wearable sensors worn by the subjects during their daily routine. This paper investigates the application of this concept to the continuous authentication of automotive vehicles, which is a novel concept in the literature and which could be used where conventional solutions based on cryptographic means could not be used. In this case, the Continuous Authentication concept is implemented using the digital output from Inertial Measurement Units (IMUs) mounted on the vehicle, while it is driving on a specific road path. Different analytical approaches based on the extraction of statistical features from the time domain representation or the use of frequency domain coefficients are compared and the results are presented for various conditions and road segments. The results show that it is possible to authenticate vehicles from the Inertial Measurement Unit (IMU) recordings with great accuracy for different road segments.

scholarly journals Estimating Movement Smoothness From Inertial Measurement Units

2021 ◽  
Vol 8 ◽  
Author(s):  
Alejandro Melendez-Calderon ◽  
Camila Shirota ◽  
Sivakumar Balasubramanian
Keyword(s):  
Motor Behavior ◽  
Reconstruction Error ◽  
Time Profile ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Movement Smoothness ◽  
Acceleration Data ◽  
Rotational Kinematics ◽  
Measurement Units ◽  
Using Data

Inertial measurement units (IMUs) are increasingly used to estimate movement quality and quantity to the infer the nature of motor behavior. The current literature contains several attempts to estimate movement smoothness using data from IMUs, many of which assume that the translational and rotational kinematics measured by IMUs can be directly used with the smoothness measures spectral arc length (SPARC) and log dimensionless jerk (LDLJ-V). However, there has been no investigation of the validity of these approaches. In this paper, we systematically evaluate the use of these measures on the kinematics measured by IMUs. We show that: (a) SPARC and LDLJ-V are valid measures of smoothness only when used with velocity; (b) SPARC and LDLJ-V applied on translational velocity reconstructed from IMU is highly error prone due to drift caused by integration of reconstruction errors; (c) SPARC can be applied directly on rotational velocities measured by a gyroscope, but LDLJ-V can be error prone. For discrete translational movements, we propose a modified version of the LDLJ-V measure, which can be applied to acceleration data (LDLJ-A). We evaluate the performance of these measures using simulated and experimental data. We demonstrate that the accuracy of LDLJ-A depends on the time profile of IMU orientation reconstruction error. Finally, we provide recommendations for how to appropriately apply these measures in practice under different scenarios, and highlight various factors to be aware of when performing smoothness analysis using IMU data.

scholarly journals Estimating Movement Smoothness from Inertial Measurement Units

2020 ◽  
Author(s):  
Alejandro Melendez-Calderon ◽  
Camila Shirota ◽  
Sivakumar Balasubramanian
Keyword(s):  
Motor Behavior ◽  
Estimation Error ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Movement Smoothness ◽  
Acceleration Data ◽  
Rotational Kinematics ◽  
Measurement Units ◽  
Using Data ◽  
Original Measure

AbstractThere is an increasing trend in using inertial measurement units (IMUs) to estimate movement quality and quantity, and infer the nature of motor behavior. The current literature contains several attempts to estimate movement smoothness using data from IMUs, most of which assume that the translational and rotational kinematics measured by IMUs can be directly used with existing smoothness measures - spectral arc length (SPARC) and log dimensionless jerk (LDLJ-V). However, there has been no investigation of the validity of these approaches. In this paper, we systematically evaluate the appropriateness of the using these measures on the kinematics measured by an IMU. We show that: (a) current measures (SPARC and LDLJ-V) are inappropriate for translational movements; and (b) SPARC and LDLJ-V can be used rotational kinematics measured by an IMU. For discrete translational movements, we propose a modified version of the LDLJ-V measure, which can be applied to acceleration data (LDLJ-A), while roughly maintaining the properties of the original measure. However, accuracy of LDLJ-A depends on the IMU orientation estimation error. We evaluate the performance of these measures using simulated and experimental data. We then provide recommendations for how to appropriately apply these measures in practice, and the various factors to be aware of when performing smoothness analysis using IMU data.

scholarly journals Validity of Wearable Sensors at the Shoulder Joint: Combining Wireless Electromyography Sensors and Inertial Measurement Units to Perform Physical Workplace Assessments

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1885 ◽  
Author(s):  
Isabelle Poitras ◽  
Mathieu Bielmann ◽  
Alexandre Campeau-Lecours ◽  
Catherine Mercier ◽  
Laurent J. Bouyer ◽  
...  
Keyword(s):  
Wearable Sensors ◽  
Correlation Coefficients ◽  
Emg Activity ◽  
Complex Task ◽  
Inertial Measurement Units ◽  
Simple Task ◽  
Inertial Measurement ◽  
Work Related ◽  
Measurement Units ◽  
Shoulder Kinematics

Background: Workplace adaptation is the preferred method of intervention to diminish risk factors associated with the development of work-related shoulder disorders. However, the majority of the workplace assessments performed are subjective (e.g., questionnaires). Quantitative assessments are required to support workplace adaptations. The aims of this study are to assess the concurrent validity of inertial measurement units (IMUs; MVN, Xsens) in comparison to a motion capture system (Vicon) during lifting tasks, and establish the discriminative validity of a wireless electromyography (EMG) system for the evaluation of muscle activity. Methods: Sixteen participants performed 12 simple tasks (shoulder flexion, abduction, scaption) and 16 complex lifting tasks (lifting crates of different weights at different heights). A Delsys Trigno EMG system was used to record anterior and middle deltoids’ EMG activity, while the Xsens and Vicon simultaneously recorded shoulder kinematics. Results: For IMUs, correlation coefficients were high (simple task: >0.968; complex task: >0.84) and RMSEs were low (simple task: <6.72°; complex task: <11.5°). For EMG, a significant effect of weight, height and a weight x height interaction (anterior: p < 0.001; middle: p < 0.03) were observed for RMS EMG activity. Conclusions: These results suggest that wireless EMG and IMUs are valid units that can be used to measure physical demand in workplace assessments.

scholarly journals Preferred Placement and Usability of a Smart Textile System vs. Inertial Measurement Units for Activity Monitoring

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2501 ◽  
Author(s):  
Mohammad Mokhlespour Esfahani ◽  
Maury Nussbaum
Keyword(s):  
Human Activity ◽  
Wearable Sensors ◽  
Activity Monitor ◽  
Activity Monitoring ◽  
Whole Body ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Wearable Technologies ◽  
Smart Textile ◽  
Measurement Units

Wearable sensors and systems have become increasingly popular in recent years. Two prominent wearable technologies for human activity monitoring are smart textile systems (STSs) and inertial measurement units (IMUs). Despite ongoing advances in both, the usability aspects of these devices require further investigation, especially to facilitate future use. In this study, 18 participants evaluate the preferred placement and usability of two STSs, along with a comparison to a commercial IMU system. These evaluations are completed after participants engaged in a range of activities (e.g., sitting, standing, walking, and running), during which they wear two representatives of smart textile systems: (1) a custom smart undershirt (SUS) and commercial smart socks; and (2) a commercial whole-body IMU system. We first analyze responses regarding the usability of the STS, and subsequently compared these results to those for the IMU system. Participants identify a short-sleeved shirt as their preferred activity monitor. In additional, the SUS in combination with the smart socks is rated superior to the IMU system in several aspects of usability. As reported herein, STSs show promise for future applications in human activity monitoring in terms of usability.

scholarly journals Validity of a Magnet-Based Timing System Using the Magnetometer Built into an IMU

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5773
Author(s):  
Carla Pérez-Chirinos Buxadé ◽  
Bruno Fernández-Valdés ◽  
Mónica Morral-Yepes ◽  
Sílvia Tuyà Viñas ◽  
Josep Maria Padullés Riu ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Short Duration ◽  
Wearable Sensors ◽  
The Other ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Future Studies ◽  
Sprint Running ◽  
Timing System ◽  
Measurement Units

Inertial measurement units (IMUs) represent a technology that is booming in sports right now. The aim of this study was to evaluate the validity of a new application on the use of these wearable sensors, specifically to evaluate a magnet-based timing system (M-BTS) for timing short-duration sports actions using the magnetometer built into an IMU in different sporting contexts. Forty-eight athletes (22.7 ± 3.3 years, 72.2 ± 10.3 kg, 176.9 ± 8.5 cm) and eight skiers (17.4 ± 0.8 years, 176.4 ± 4.9 cm, 67.7 ± 2.0 kg) performed a 60-m linear sprint running test and a ski slalom, respectively. The M-BTS consisted of placing several magnets along the course in both contexts. The magnetometer built into the IMU detected the peak-shaped magnetic field when passing near the magnets at a certain speed. The time between peaks was calculated. The system was validated with photocells. The 95% error intervals for the total times were less than 0.077 s for the running test and 0.050 s for the ski slalom. With the M-BTS, future studies could select and cut the signals belonging to the other sensors that are integrated in the IMU, such as the accelerometer and the gyroscope.

Prediction of human gait activities using wearable sensors

2021 ◽  
pp. 095441192110012
Author(s):  
Ahmed Halim ◽  
A. Abdellatif ◽  
Mohammed I Awad ◽  
Mostafa RA Atia
Keyword(s):  
Prediction Accuracy ◽  
Gait Cycle ◽  
Wearable Sensors ◽  
Machine Learning Algorithms ◽  
Human Gait ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Acceptable Accuracy ◽  
Prediction Time ◽  
Measurement Units

This paper aims to enhance the accuracy of human gait prediction using machine learning algorithms. Three classifiers are used in this paper: XGBoost, Random Forest, and SVM. A predefined dataset is used for feature extraction and classification. Gait prediction is determined during several locomotion activities: sitting (S), level walking (LW), ramp ascend (RA), ramp descend (RD), stair ascend (SA), stair descend (SD), and standing (ST). The results are gained for steady-state (SS) and overall (full) gait cycle. Two sets of sensors are used. The first set uses inertial measurement units only. The second set uses inertial measurement units, electromyography, and electro-goniometers. The comparison is based on prediction accuracy and prediction time. In addition, a comparison between the prediction times of XGBoost with CPU and GPU is introduced due to the easiness of using XGBoost with GPU. The results of this paper can help to choose a classifier for gait prediction that can obtain acceptable accuracy with fewer types of sensors.

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