Machine Learning Applied to Datasets of Human Activity Recognition-An Applications of Data Analysis in HealthCare

Background: Older adults who have poor health, such as those in personal conditions motivate them to remain active and productive, both at home and in geriatric homes, they need a combination of advanced methods of visual monitoring, optimization, pattern recognition and learning, that provide safe and comfortable environments and that once serve as a tool to facilitate the work of family members and workers. It should be noted that this also seeks to recreate a technology that gives these adults autonomy in indoor environments. Objective: Generate a prediction model of activities of daily living through classification techniques and selection of characteristics, to contribute to the development in this area of knowledge, especially in the field of health, to carry out an accurate monitoring of activities of the elderly or people with some type of disability. Technological developments allow predictive analysis of activities of daily life, contributing to the identification of patterns in advance, to take actions to improve the quality of life of the elderly. Method: The vanKasteren, CASAS Kyoto and CASAS Aruba datasets were used, which have certain variability in terms of occupation and the number of activities of daily life to be identified, to validate a predictive model capable of supporting their identification. activities in indoor environments. Results: After implementing 12 classifiers, among which the following stand out: Classification Via Regression, OneR, Attribute Selected, J48, Random SubSpace, RandomForest, RandomCommittee, Bagging, Random Tree, JRip, LMT and REP Tree, are analyzed in the light of precision and recall quality metrics, those classifiers that show better results when identifying activities of daily life. For the specific case of this experimentation, the Classification Via Regression and OneR classifiers obtain the best results. Conclusion: The efficiency of the predictive model based on classification is concluded, showing the results of the two classifiers Classification Via Regression and OneR with quality metrics higher than 90% even when the datasets vary in occupation and number of activities

LA COMPENSACIÓN DE CULPAS A LA LUZ DEL ARTÍCULO 2330 DEL CÓDIGO CIVIL. UNA REVISIÓN A PROPÓSITO DE LA SENTENCIA DE LA CORTE SUPREMA CAUSA ROL 39484-2017

The participation of the injured party in cases of tortious liability is fundamentally regulated in article 2330 of the Bello Code. This rule allows the reduction of the sentence if the tort, committed by the tortfeasor, has been joined by reckless participation of the injured party. In such interference, by act or omission, a desertion of its duty to discharge is supposed, the problem must be treated as a matter of fault in the measure that this implies the distribution of a part of the social risks linked to the activities of daily life. Currently, there is a large national doctrine that addresses the matter set forth. Consequently, adhering to it, we will analyse the decision of the court, contributing with critical and personal reasoning regarding this subject.

Frequency of Text Neck Pain in Islamabad

Background: Neck pain is one of the most common musculoskeletal condition and causes most disability. Neck pain with movement coordinated impairments is the most common problem and among them “Text Neck Pain” is most growing epidemiological problem among adult population. Methods: This was the cross sectional study. The sample was collected from different Colleges and Universities of Islamabad. Sample was selected using convenient non-probability sampling technique. Data was collected from 428 individuals of both genders and analyzed through SPSS-21. Individual’s basic demographics name, age, gender etc. and other relevant information was taken through a self-structured questionnaire. Two standard questionnaires were also used for taking statistical data about pain intensity via numeric pain rating scale (NPRS) and level of disability through neck pain disability index (NPDI). Results: The mean age of the research participants was 22.74 ± 3.52 years. The results showed that 35.0% of the smart phone users feel neck pain regularly and 39.5 % of the population sometimes feel pain in the activities of daily life. Results also showed that majority of the population having neck pain use the cell phone in sitting position at an angle of 30-45 degrees of neck flexion for more than 3 hours/day. Conclusion: It is concluded that individuals having more use of smart phones have more text neck pain which is also affecting their activities of daily life. So, it’s the alarming situation for the adults.

Paving the Way Toward Distinguishing Fallers From Non-fallers in Bilateral Vestibulopathy: A Wide Pilot Observation

Patients with bilateral vestibulopathy (BVP) present with unsteadiness during standing and walking, limiting their activities of daily life and, more importantly, resulting in an increased risk of falling. In BVP patients, falls are considered as one of the major complications, with patients having a 31-fold increased risk of falling compared to healthy subjects. Thus, highlighting objective measures that can easily and accurately assess the risk of falling in BVP patients is an important step in reducing the incidence of falls and the accompanying burdens. Therefore, this study investigated the interrelations between demographic characteristics, vestibular function, questionnaires on self-perceived handicap and balance confidence, clinical balance measures, gait variables, and fall status in 27 BVP patients. Based on the history of falls in the preceding 12 months, the patients were subdivided in a “faller” or “non-faller” group. Results on the different outcome measures were compared between the “faller” and “non-faller” subgroups using Pearson's chi-square test in the case of categorical data; for continuous data, Mann–Whitney U test was used. Performances on the clinical balance measures were comparable between fallers and non-fallers, indicating that, independent from fall status, the BVP patients present with an increased risk of falling. However, fallers tended to report a worse self-perceived handicap and confidence during performing activities of daily life. Spatiotemporal parameters of gait did not differ between fallers and non-fallers during walking at slow, preferred, or fast walking speed. These results may thus imply that, when aiming to distinguish fallers from non-fallers, the BVP patients' beliefs concerning their capabilities may be more important than the moderately or severely affected physical performance within a clinical setting. Outcome measures addressing the self-efficacy and fear of falling in BVP patients should therefore be incorporated in future research to investigate whether these are indeed able to distinguish fallers form non-fallers. Additionally, information regarding physical activity could provide valuable insights on the contextual information influencing behavior and falls in BVP.

Predictive potentials of 8 muscle strength actions, KOOS-pain, and Örebro-psychosocial difficulties on self-reported activities-of-daily-life function in patients with knee osteoarthritis: an exploratory regression-based cross-sectional study

The authors have requested that this preprint be withdrawn due to author disagreement.