A smart textile sleeve for rehabilitation of knee injuries

Haladjian, Juan; Scheuermann, Constantin; Bredies, Katharina; Bruegge, Bernd

doi:10.1145/3123024.3123151

Cited by 7 publications

(4 citation statements)

References 5 publications

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“…In other works [ 6 , 18 , 20 , 21 ], piezoresistive matrix-type sensors have been used as normal pressure sensors. Figure 5 shows the output characteristic of a single matrix point of the smart textile in this work under varying pressure.…”

Section: Experimental Validationmentioning

confidence: 99%

“…In a medical context, electrodes can be integrated in clothing to monitor electrical activity in the body manifesting as electromyographic (EMG) [ 2 ], electrocardiagraphic (ECG) [ 3 ], or electroencephalographic (EEG) [ 4 ] signals, or to induce electrical currents as a form of electrotherapy [ 5 ]. Another example is KneeHapp [ 6 ], a system to oversee the rehabilitation of knee injuries that is able to measure muscle shake, pressure on the foot, and bending angles of the leg using inertial measurement units and piezoresistive sensing. Unobtrusive health monitoring can also benefit healthy persons working dangerous jobs: Ref.…”

Section: Introductionmentioning

confidence: 99%

“…In other work [ 15 , 16 , 17 , 18 , 19 , 20 , 21 ], smart textiles have additionally been used for classification tasks in the field of robotics. In [ 18 ], flexible piezoresistive pressure sensors similar to the one in [ 6 ] are applied to a robotic gripper, enabling it to recognize different objects by grasping them. The same sensing principle is explored in detail in [ 21 ], with a specific focus on cross-talk cancellation and with intended applications in soft robotics.…”

Section: Introductionmentioning

confidence: 99%

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Modular Piezoresistive Smart Textile for State Estimation of Cloths

Proesmans

Verleysen

Vleugels

et al. 2021

Sensors

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Smart textiles have found numerous applications ranging from health monitoring to smart homes. Their main allure is their flexibility, which allows for seamless integration of sensing in everyday objects like clothing. The application domain also includes robotics; smart textiles have been used to improve human-robot interaction, to solve the problem of state estimation of soft robots, and for state estimation to enable learning of robotic manipulation of textiles. The latter application provides an alternative to computationally expensive vision-based pipelines and we believe it is the key to accelerate robotic learning of textile manipulation. Current smart textiles, however, maintain wired connections to external units, which impedes robotic manipulation, and lack modularity to facilitate state estimation of large cloths. In this work, we propose an open-source, fully wireless, highly flexible, light, and modular version of a piezoresistive smart textile. Its output stability was experimentally quantified and determined to be sufficient for classification tasks. Its functionality as a state sensor for larger cloths was also verified in a classification task where two of the smart textiles were sewn onto a piece of clothing of which three states are defined. The modular smart textile system was able to recognize these states with average per-class F1-scores ranging from 85.7 to 94.6% with a basic linear classifier.

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Section: Experimental Validationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modular Piezoresistive Smart Textile for State Estimation of Cloths

Proesmans

Verleysen

Vleugels

et al. 2021

Sensors

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“…The compact size and wireless capabilities make it a versatile and practical tool in clinical and research settings. Only a few of these have been used in rehabilitation settings following injury or surgery and have been able to measure the hop height, width and sagittal plane angles reliably [23][24][25]. One of these IMU systems (OPED Corp., Valley, Germany) was validated and shown to be highly correlated with well-established measurement devices [26].…”

Section: Introductionmentioning

confidence: 99%

A Single-Leg Vertical Hop Test Is an Effective Tool to Measure Functional Performance after Anterior Cruciate Ligament (ACL) Reconstruction

Höher,

Ostner,

Schraplau

et al. 2024

Applied Sciences

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This study evaluated the single-leg vertical hop test (SLVHT), using digital sensor technology, for the functional assessment of rehabilitation progress in patients after ACL reconstruction (ACL-R). Between January 2019 and June 2022, 143 patients (26.6 (8.9) years, m/f 66/34%) completed return-to-sport testing at 3 and 6 months after ACL-R. The jump height during SLVHT was quantified with a digital motion sensor, containing a three-axis acceleration gyroscope sensor, and the limb symmetry index (LSI) (injured/non-injured leg ratio) was calculated. Three months postoperatively, the jump height of the injured leg was 59.6% (13.5 (5.5) cm) that of the non-injured leg (22.9 (6.2) cm; p < 0.01). After 6 months, the jump height of the injured leg (18.4 (6.9) cm) improved by 44.1% compared to that at the 3-month follow-up but was still lower than the non-injured leg jump height (23.2 (7.0) cm, p < 0.001; LSI = 79.6%). Men jumped higher than women, but their LSI was not different at 3 (59.6 vs. 59.5%) and 6 months (80.6 vs. 77.8%). Regression analysis identified the non-injured leg jump height as the primary independent predictor of the jump height of the injured leg (β = 0.776, T = 51.506, p < 0.001). SLVHT, using digital sensor technology, is a simple and cost-effective functional test to assess rehabilitation progress after ACL-R, with the potential for multi-centre data analysis.

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