C Practitioners in the field encounter clients who are struggling with real-life situations and issues. It is critical that practitioners are able to intervene and help clients understand and identify their disorders, and the ways in which they can be treated. In this case study exercise, you will be able to conduct research on a common disorder, discuss possible interventions, and discuss how faith affects this disorder.
Scenario: Sarahâs Sleep Dilemma
You have a client/patient named Sarah, who is struggling with sleep issues. She is only able to sleep for 4â5 hours per night. She falls asleep easily, but awakens after 5 hours, and finds herself unable to fall back asleep after that. In her life, she is struggling with many challenges at home, work and school, and she finds it difficult to shut down when bedtime comes. Sarah is experiencing a very common disorder â insomnia. As a result, many areas of her life have been affected: school, work, and relationships.
Assignment Instructions
Research the insomnia disorder.
Describe the typical symptoms of insomnia.
Describe the disorderâs physiological impact.
Does gender and culture play a role in the disorder?
Describe one medical intervention used to treat insomnia.
Medication
Homeopathic
Dietary
Describe one psychological intervention used to treat insomnia.
Analyze possible ethical implications to the medical and psychological interventions described earlier.
Analyze faithâs effect on the disorder.
What role does faith play?
Does faith help or intensify the disorder?
Assignment Requirements
Description of the typical symptoms of insomnia
Description of the physiological impact on the disorder
Description of one medical intervention used to treat insomnia
Description of one psychological intervention used to treat insomnia
Analysis of possible ethical implications from the medical and psychological interventions described earlier.
Analysis of faithâs effect on the disorder.
Sample Solution
ter on, one of the most known methods will be discussed in a detailed way. The facial recognition methods that can be used, all have a different approach. Some are more frequently used for facial recognition algorithms than others. The use of a method also depends on the needed applications. For instance, surveillance applications may best be served by capturing face images by means of a video camera while image database investigations may require static intensity images taken by a standard camera. Some other applications, such as access to top security domains, may even necessitate the forgoing of the nonintrusive quality of face recognition by requiring the user to stand in front of a 3D scanner or an infrared sensor[15]. Consequently, there can be concluded that there can be made a division of three groups of face recognition techniques, depending on the wanted type of data results, i.e. methods that compare images, methods that look at data from video cameras and methods that deal with other sensory data, like 3D pictures or infrared imagery. All of them can be used in different ways, to prevent crime from happening or recurring. ii. How do these technologies work? As listed above, there exists a long list of methods and algorithms that can be used for facial recognition. Four of them are used frequently and are most known in the literature, i.e. Eigenface Method, Correlation Method, Fisherface Method and the Linear Subspaces Method. But how do these facial recognition work? Because of word limitations, only one of those four facial recognition techniques, i.e The Eigenface Method, will be discussed. Hopefully this will give an general idea of how facial recognition works and can be used. One of the major difficulties of facial recognition, is that you have to cope with the fact that a personâs appearance may change, such that the two images that are being compared differentiate too much from each other. Also environmental changes in pictures, like lightning, have to be taken into account, in order to have successful facial recognition. Thus from a picture of a face, as well as from a live face, some yet more abstract visual representation must be established which can mediate recognition despite the fact that in real life the same face will hardl>
ter on, one of the most known methods will be discussed in a detailed way. The facial recognition methods that can be used, all have a different approach. Some are more frequently used for facial recognition algorithms than others. The use of a method also depends on the needed applications. For instance, surveillance applications may best be served by capturing face images by means of a video camera while image database investigations may require static intensity images taken by a standard camera. Some other applications, such as access to top security domains, may even necessitate the forgoing of the nonintrusive quality of face recognition by requiring the user to stand in front of a 3D scanner or an infrared sensor[15]. Consequently, there can be concluded that there can be made a division of three groups of face recognition techniques, depending on the wanted type of data results, i.e. methods that compare images, methods that look at data from video cameras and methods that deal with other sensory data, like 3D pictures or infrared imagery. All of them can be used in different ways, to prevent crime from happening or recurring. ii. How do these technologies work? As listed above, there exists a long list of methods and algorithms that can be used for facial recognition. Four of them are used frequently and are most known in the literature, i.e. Eigenface Method, Correlation Method, Fisherface Method and the Linear Subspaces Method. But how do these facial recognition work? Because of word limitations, only one of those four facial recognition techniques, i.e The Eigenface Method, will be discussed. Hopefully this will give an general idea of how facial recognition works and can be used. One of the major difficulties of facial recognition, is that you have to cope with the fact that a personâs appearance may change, such that the two images that are being compared differentiate too much from each other. Also environmental changes in pictures, like lightning, have to be taken into account, in order to have successful facial recognition. Thus from a picture of a face, as well as from a live face, some yet more abstract visual representation must be established which can mediate recognition despite the fact that in real life the same face will hardl>
