Arthroscopic repair of rotator cuff injury with bioabsorbable suture anchor vs. all-suture anchor: a non-inferiority study.

BACKGROUND: Compare all-suture anchors to traditional anchors through clinical and radiological evaluation at pre-established end-points. MATERIALS AND METHODS: We performed a two-arms non-inferiority study on all-suture anchor (2.3 iconix™, Stryker) device with respect to traditional anchor (5.5 healix Advance™ BR, Depuy/Mitek) device under unpaired samples with size equal to 30 patients per group, all suffering from supraspinatus tendon rupture. We administrated DASH (Disabilities of the Arm, Shoulder and Hand); constant; and SST (Simple Shoulder Test) questionnaires in pre-operative, 3 ± 1 months post-intervention and 8 ± 1 months post-intervention. Questionnaires scores were the primary outcome. We also evaluated RMI at 3 and at 8 months after surgery to assess the presence of oedema or any loosening of the implant. RESULTS: All-suture anchor approach has been proven to have non-inferior performances with respect to traditional anchor approach, according to questionnaires scores at the 3-month endpoint. We observed 26 patients with oedema by MRI (18 in control group, 6 in experimental group). In the 8-month endpoint we found persistent edema in 12 patients (all treated with healix), 2 had mobilitazions (healix), 10 had partial retears (8 healix, 2 iconix) and 1 implant failure (healix). CONCLUSIONS: All suture devices have clinical and functional results comparable to traditional devices, while they tend to give fewer complications in terms of bone edema, loosening and retear rate. The effectiveness of all-suture devices should be further investigated in rotator cuff suture arthroscopic revision surgery, given the advantages they offer.

Sensor Effects in LCL-Type Grid-Connected Shunt Active Filters Control Using Higher-Order Sliding Mode Control Techniques.

The effects of measuring devices/sensors on improving the power quality (PQ) of electric networks are studied in this paper. In this context, improving the performance of an LCL-type grid connected to a three-phase three-wire shunt active filter (SAF) in the presence of voltage perturbations is studied. In order to ensure the high-quality performance of LCL-SAF in the presence of voltage perturbations, the robust continuous second-order sliding mode controller (2-SMC), including twisting and super-twisting controllers, and continuous higher-order sliding mode controller (C-HOSMC)-based approaches are employed. These controllers, whose outputs are processed by pulse-width modulation (PWM), allow minimization of the phase shift and prevent the generation of discontinuous chattering commands, which can severely damage the VSI components. Moreover, an integration of a generalized instantaneous power identification algorithm with an advanced phase locked loop (PLL) was proposed and experimentally tested to validate the effective performances of SAF under severe perturbations. Additionally, the studied approaches were tested via simulations taking into account a conventional nonlinear industrial load in a real textile factory environment, using measurements provided by power quality analyzers. Finally, the effects of the measuring devices, including the current and voltage sensors, on the accuracy and reliability of the SAF and, consequently, on the PQ of the electric power grid were studied via simulations and experimentally. The results of this study support the validity of the recently published patent.

Online Condition Monitoring of Bearings to Support Total Productive Maintenance in the Packaging Materials Industry.

The packaging materials industry has already recognized the importance of Total Productive Maintenance as a system of proactive techniques for improving equipment reliability. Bearing faults, which often occur gradually, represent one of the foremost causes of failures in the industry. Therefore, detection of their faults in an early stage is quite important to assure reliable and efficient operation. We present a new automated technique for early fault detection and diagnosis in rolling-element bearings based on vibration signal analysis. Following the wavelet decomposition of vibration signals into a few sub-bands of interest, the standard deviation of obtained wavelet coefficients is extracted as a representative feature. Then, the feature space dimension is optimally reduced to two using scatter matrices. In the reduced two-dimensional feature space the fault detection and diagnosis is carried out by quadratic classifiers. Accuracy of the technique has been tested on four classes of the recorded vibrations signals, i.e., normal, with the fault of inner race, outer race, and ball operation. The overall accuracy of 98.9% has been achieved. The new technique can be used to support maintenance decision-making processes and, thus, to increase reliability and efficiency in the industry by preventing unexpected faulty operation of bearings.

Detection of epileptiform activity in EEG signals based on time-frequency and non-linear analysis.

We present a new technique for detection of epileptiform activity in EEG signals. After preprocessing of EEG signals we extract representative features in time, frequency and time-frequency domain as well as using non-linear analysis. The features are extracted in a few frequency sub-bands of clinical interest since these sub-bands showed much better discriminatory characteristics compared with the whole frequency band. Then we optimally reduce the dimension of feature space to two using scatter matrices. A decision about the presence of epileptiform activity in EEG signals is made by quadratic classifiers designed in the reduced two-dimensional feature space. The accuracy of the technique was tested on three sets of electroencephalographic (EEG) signals recorded at the University Hospital Bonn: surface EEG signals from healthy volunteers, intracranial EEG signals from the epilepsy patients during the seizure free interval from within the seizure focus and intracranial EEG signals of epileptic seizures also from within the seizure focus. An overall detection accuracy of 98.7% was achieved.