Day 1
10:00- 10:05 am
by Abhijit Das
10:05 - 11:05 am
Speaker: Ziyan Wu, Sr. Director of Vision and Robotics UII America
Chair: Abhijit Das
Abstract. Medical scanners are widely used in screening and diagnosis in order to develop a personalized treatment plan for patients. Current patient examination workflow with medical scanners comprises several critical pre-scan events that involve manual operations and physical interactions between patients and medical professionals such as directing patients to the examination room, assisting them to pose according to scanning protocols, and positioning them for the scan, which may increase the risk for infection. This talk will cover several computer vision algorithms and systems we developed to make medical scanners more intelligent and efficient by automating the scanning procedure, as well as real-world examples of their applications.
Chair: Abhijit Das
11:05 - 11:45 am
O1: Investigating Visual Features for Cognitive Impairment Detection Using In-the-wild Data
O2: Pain Detection in Masked Faces during Procedural Sedation
11:45 am - 12:45 pm
Speaker: Vitaly Herasevich, Professor of Anesthesiology & Medicine Mayo Clinic
Chair: Srijan Das
Abstract: Video recording and video recognition with computer vision have become widely used in many aspects of modern life. Hospitals have employed VR technology for security purposes, however, despite the growing number of studies showing the feasibility of VR software for physiologic monitoring or detection of patient abnormality its use in the hospital in real-time is sparse and the perception of this novel technology is unknown.
This lecture provides background and discuss aspects of technology acceptance by clinical providers, patients, and patient’s families.
Chair: Francois Bremond
12: 45 - 1:25 pm
O3: New Insights on Weight Estimation from Face Images
O4: Automatic Assessment of Infant Face and Upper-Body Symmetry as Early Signs of Torticollis
1:25 - 2:25 pm
Speaker: Surangama Dasgupta, Medical Practitioner and dancer, Director of Deodar Suchanda Sangitalaya, Guest professor at Justus Liebig University, Giessen, Germany
Chair: Antitza Dantcheva
Abstract: This talk addressed the role of music, dance therapy through cognitive Assessment across diverse populations through Expressive Therapy with a special focus on the active and passive involvement of the clients.
Through Psychotherapy an individual can increase the sense of his or her well-being and it is designed to improve the mental health of a client. Balanced emotional development is related to cognitive and sensory-motor development. In Natyashastra, the aesthetic theory of Indian Music that is Sangeet is ‘Ananda’ or ultimate joy. Implementing this theory combining the process of Psychoanalysis in which abreaction or repressed negative emotion gets a healthy outlet and it also facilitates catharsis through free association. Cognitive behaviour therapy (CBT) is a form of therapy which helps the clients to overcome their symptoms by changing their thinking, behaviour and emotional responses.
Mudra or hand gestures form one of the most significant aspects of Indian performing art and can be used as a learning mechanism which helps in increasing and building up concentration and attention among clients. During therapy, the involvement of the client may vary according to the client’s personality and emotional state. Those who are expressive and outspoken prefer to have Active participation, being emotionally involved in the process. On the other hand, a client who is too conscious about one's performance, prefers to remain aloof from active involvement, they are passive. In that case, the therapist helps him/her to listen and observe different genres of the client’s choice, helping to realize the innate disturbance and thus get rid of the negative emotional state of mind.
These findings thus propose the use of Artificial Intelligence to generate unbiased, accurate, objective, yet client-based, personalized therapeutic models. AI can evade therapist-centric biases and subjectivities in the case of one-to-one consultations, and can even break the ice more easily with passive clients. Such models can help practitioners garner better data and address wider groups and communities, further enhancing the knowledge base of the model and the effectiveness of the therapy over time.
2:25 - 2:30