[The AO/ASIF Flexnail : A flexible intramedullary nail for the treatment of humeral shaft fractures]

BACKGROUND: The use of conventional implants for intramedullary nailing of humeral shaft fractures is associated with specific difficulties. During antegrade implantation structures of the rotator cuff can be affected leading to a reduced functional result of the shoulder. If the nail is implanted in a retrograde manner problems arise due to a relatively large hole close to or within the olecranon fossa, which is necessary for insertion of the nail. Supracondylar fractures as well as persistent elbow pain and loss of function are reported in the literature. To overcome these disadvantages a flexible nail has been developed that can be stiffened and locked after implantation. METHOD: Between October 2000 and February 2002, 34 patients were treated with the flexible nail at our institution; 29 were available for follow-up. Fracture healing was documented on radiographs and clinical outcome was evaluated with use of the Constant as well as the Kwasny score. RESULTS: Median duration until fracture consolidation was 10 weeks. In two patients fracture union was not achieved within the follow-up period. The median outcome measured with the Constant score was 93 points and 2.5 with the Kwasny score. Both values correspond to a very good functional outcome. CONCLUSION: We conclude that the flexible humeral nail is an excellent treatment option for humeral shaft fractures. Damage to the rotator cuff and the distal humerus can be avoided due to its unique flexible construction, improving the functional outcome of intramedullary nailing for the treatment of humeral shaft fractures.

Fabrication methods for creating flexible polymer substrate sensor tags

The authors describe the design, fabrication, and testing of a passive wireless sensor platform utilizing low-cost commercial surface acoustic wave filters and sensors. Polyimide and polyethylene terephthalate sheets are used as substrates to create a flexible sensor tag that can be applied to curved surfaces. A microfabricated antenna is integrated on the substrate in order to create a compact form factor. The sensor tags are fabricated using 315 MHz surface acoustic wave filters and photodiodes and tested with the aid of a fiber-coupled tungsten lamp. Microwave energy transmitted from a network analyzer is used to interrogate the sensor tag. Due to an electrical impedance mismatch at the SAW filter and sensor, energy is reflected at the sensor load and reradiated from the integrated antenna. By selecting sensors that change electrical impedance based on environmental conditions, the sensor state can be inferred through measurement of the reflected energy profile. Testing has shown that a calibrated system utilizing this type of sensor tag can detect distinct light levels wireless and passively. The authors also demonstrate simultaneous operation of two tags with different center passbands that detects light. Ranging tests show that the sensor tags can operate at a distance of at least 3.6 m.

Learning flexible sensori-motor mappings in a complex network

Given the complex structure of the brain, how can synaptic plasticity explain the learning and forgetting of associations when these are continuously changing? We address this question by studying different reinforcement learning rules in a multilayer network in order to reproduce monkey behavior in a visuomotor association task. Our model can only reproduce the learning performance of the monkey if the synaptic modifications depend on the pre- and postsynaptic activity, and if the intrinsic level of stochasticity is low. This favored learning rule is based on reward modulated Hebbian synaptic plasticity and shows the interesting feature that the learning performance does not substantially degrade when adding layers to the network, even for a complex problem.