Introduction: Sub-Saharan Africa (SSA) has the highest stroke prevalence along with a case fatality that amounts to 40%. We aimed to assess the effect of a minimal setting stroke unit in SSA Public hospital on stroke mortality and main medical complications. Materials and Methods: The study was set in Conakry, Guinea, Ignace Deen public referral hospital. Clinical characteristics, hospital mortality and main medical stroke complications rates (pneumonia, urinary tract infections, sores and venous thromboembolism) of admitted stroke patients after the installation of a minimal stroke unit equipped with heart rate, blood pressure and blood oxygen saturation monitoring and portable oxygen concentrator (POST) were compared to a similar number of stroke patients admitted before the stroke unit creation (PRE). Results: PRE ( n = 318) and POST ( n = 361) stroke, patients were comparable in term of age (61 ± 14 vs. 60 ± 14.8 years, p = 0.24), sex (56 vs. 50% males, p = 0.09), High blood pressure rate (76.7 vs. 79%, p = 0.44), stroke subtype (ischemic in 72 vs. 78% of cases, p = 0.05) and NIHSS (11 ± 4 vs. 11 ± 4, p = 0.85). Diabetes was more frequent in the PRE group (19 vs. 9%, p < 0.001). Mortality was significantly lower in the POST group (7.2 vs. 22.3%, p < 0.0001) as well as medical complications (4.1 vs. 27.7%, p < 0.001) and lower pneumonia rate (3.3 vs. 14.5%, p < 0.001). Conclusions: Minimally equipped stroke units significantly reduce stroke mortality and main medical complications in SSA.

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Problem statement: The sensor for image control point in Face Recognition (FR) is one of the most active research areas in computer vision and pattern recognition. Its practical application includes forensic identification, access control and human computer interface. The task of a FR system is to compare an input face image against a database containing a set of face samples with known identity and identifying the subject to which the input face belongs. However, a straightforward implementation is difficult since faces exhibit significant variations in appearance due to acquisition, illuminations, pose and aging variations. This research contracted with several images combined through image registration offering the possibility of improving eigenface recognition. Sensor detection by head orientation for image control point of the training sets collected in a database was discussed. Approach: In fact, the aim of such a research consisted first, identification of the face recognition and the possibility of improving eigenface recognition. So the approach of eigenface focused on three fundamental points: generating eigenfaces, classification and identification and the method used image processing toolbox to perform the matrix calculations. Results: Observation showed that the performance of the proposed technique proved to be less affected by registration errors. Conclusion/Recommendations: We presented the intelligent sensor for face recognition using image control point of eigenfaces. It is important to note that many applications of face recognition do not require perfect identification, although most require a low false-positive rate. In searching a large database of faces, for example, it may be preferable to find a small set of likely matches to present to the user

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