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1.
J Neuroeng Rehabil ; 19(1): 22, 2022 02 20.
Article in English | MEDLINE | ID: mdl-35184727

ABSTRACT

BACKGROUND: The ability to measure joint kinematics in natural environments over long durations using inertial measurement units (IMUs) could enable at-home monitoring and personalized treatment of neurological and musculoskeletal disorders. However, drift, or the accumulation of error over time, inhibits the accurate measurement of movement over long durations. We sought to develop an open-source workflow to estimate lower extremity joint kinematics from IMU data that was accurate and capable of assessing and mitigating drift. METHODS: We computed IMU-based estimates of kinematics using sensor fusion and an inverse kinematics approach with a constrained biomechanical model. We measured kinematics for 11 subjects as they performed two 10-min trials: walking and a repeated sequence of varied lower-extremity movements. To validate the approach, we compared the joint angles computed with IMU orientations to the joint angles computed from optical motion capture using root mean square (RMS) difference and Pearson correlations, and estimated drift using a linear regression on each subject's RMS differences over time. RESULTS: IMU-based kinematic estimates agreed with optical motion capture; median RMS differences over all subjects and all minutes were between 3 and 6 degrees for all joint angles except hip rotation and correlation coefficients were moderate to strong (r = 0.60-0.87). We observed minimal drift in the RMS differences over 10 min; the average slopes of the linear fits to these data were near zero (- 0.14-0.17 deg/min). CONCLUSIONS: Our workflow produced joint kinematics consistent with those estimated by optical motion capture, and could mitigate kinematic drift even in the trials of continuous walking without rest, which may obviate the need for explicit sensor recalibration (e.g. sitting or standing still for a few seconds or zero-velocity updates) used in current drift-mitigation approaches when studying similar activities. This could enable long-duration measurements, bringing the field one step closer to estimating kinematics in natural environments.


Subject(s)
Lower Extremity , Walking , Biomechanical Phenomena , Humans , Range of Motion, Articular , Rotation
2.
J Phys Chem Lett ; 6(6): 1071-5, 2015 Mar 19.
Article in English | MEDLINE | ID: mdl-26262872

ABSTRACT

p-Type metal-oxide hole transport layer (HTL) suppresses recombination at the anode and hence improves the organic photovoltaic (OPV) device performance. While NiOx has been shown to exhibit good HTL performance, very thin films (<10 nm) are needed due to its poor conductivity and high absorption. To overcome these limitations, we utilize CuGaO2, a p-type transparent conducting oxide, as HTL for OPV devices. Pure delafossite phase CuGaO2 nanoplates are synthesized via microwave-assisted hydrothermal reaction in a significantly shorter reaction time compared to via conventional heating. A thick CuGaO2 HTL (∼280 nm) in poly(3-hexylthiophene):[6,6]-phenyl-C61-butyric acid methyl ester (P3HT:PCBM) devices achieves 3.2% power conversion efficiency, on par with devices made with standard HTL materials. Such a thick CuGaO2 HTL is more compatible with large-area and high-volume printing process.

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