Feasibility of using Gyroscope to Derive Keys for Mobile Phone and Smart Wearable

Liu, Yuanzhen; Boshoff, Dutliff; Hancke, Gerhard P.

doi:10.1109/indin51773.2022.9976092

Cited by 4 publications

(1 citation statement)

References 25 publications

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“…IMUs, such as those embedded in running watches and smartphones, are inexpensive and feasible to use in field-based settings. They provide kinematic data only for their attachment points, but they typically sample at frequencies of 400–500 Hz [ 29 ] and therefore accumulate a large amount of data over a short time. In the interest of data reduction, some studies extract a few features from the raw signal’s time domain, such as the maximum angle of a segment or peak accelerations, which capture some, but not all, aspects of running kinematics.…”

Section: Introductionmentioning

confidence: 99%

Predicting Tissue Loads in Running from Inertial Measurement Units

Rasmussen,

Skejø,

Waagepetersen

2023

Sensors

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Background: Runners have high incidence of repetitive load injuries, and habitual runners often use smartwatches with embedded IMU sensors to track their performance and training. If accelerometer information from such IMUs can provide information about individual tissue loads, then running watches may be used to prevent injuries. Methods: We investigate a combined physics-based simulation and data-based method. A total of 285 running trials from 76 real runners are subjected to physics-based simulation to recover forces in the Achilles tendon and patella ligament, and the collected data are used to train and test a data-based model using elastic net and gradient boosting methods. Results: Correlations of up to 0.95 and 0.71 for the patella ligament and Achilles tendon forces, respectively, are obtained, but no single best predictive algorithm can be identified. Conclusions: Prediction of tissues loads based on body-mounted IMUs appears promising but requires further investigation before deployment as a general option for users of running watches to reduce running-related injuries.

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Section: Introductionmentioning

confidence: 99%