Iot Based Smart Poultry Farming using Commodity Hardware and Software

  • Handigolkar L
  • Kavya M
  • Veena P
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Abstract

The recruitment characteristics of muscle selective nerve stimulation by a multi-contact nerve cuff electrode, as predicted by computer modeling, have been investigated in acute experiments on rabbits. A nerve cuff containing five or six dot electrodes was placed around the sciatic nerve in five rabbits. M-waves were recorded with wire electrodes from the lateral gastrocnemius, soleus, tibialis anterior, and extensor digitorum longus muscles. The muscle recruitment performances of three contact configurations (monopole, transverse bipole, transverse tripole) were compared. The selectivity was quantified by the recruitment of two muscles (one extensor and one flexor) in response to a particular stimulus. The results showed that only in a few cases, transverse bi- and tripolar stimulation provided a better selectivity than monopolar stimulation. Neither of the two extensors, nor of the two flexors could be stimulated separately. In accordance with the results of the modeling studies, bi- and tripolar stimulation required higher stimulus currents than monopolar stimulation, whereas maximum recruitment and slopes of recruitment curves were lower. The rabbit sciatic nerve appears to be a less suitable preparation for reproducible selectivity experiments, due to the variability in the number and size of the fascicles and their position in this nerve.

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Handigolkar, L. S., Kavya, M. L., & Veena, P. D. (2016). Iot Based Smart Poultry Farming using Commodity Hardware and Software. Bonfring International Journal of Software Engineering and Soft Computing, 6(Special Issue), 171–175. https://doi.org/10.9756/bijsesc.8269

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