# Report of the 2017 IEEE Cyber Science and Technology Congress
## 6 Cyber-Enabled Smart Environment and Healthcare  
This special session has seven papers on various topics related to smart environment and healthcare. We also included two papers from the short paper session because they are also related to healthcare.  
In [36], [PERSON] et al. described an inexpensive system that can be used to carry out balance assessment. It uses a set of high speed cameras and a Wii balance board with custom software to determine the center of mass and the center of pressure. They validated their system experimentally with reasonably good result.  
In [37], [PERSON] and [PERSON] proposed a system designed to serve as a virtual life coach for children with autism. They argued that the content of the treatment/care program should be designed to cater to the intense interests of each autism child so that he/she is more responsive to the treatment and care programs. They provided a detailed description of major components of the system.  
In [38], [PERSON] and [PERSON] reported their customer validation experiences on the technology they developed as part of an Ohio i-Corps program. The technology was initially designed to track non-compliance activities such as back bending that might increase the risk of lower back injuries of nursing assistants [39; 40; 41]. Through numerous interviews with potential customers during the customer validation study, they realized that the technology can be evolved into a digital platform that track the quality of services provided by nursing assistants, and therefore, can be used to build an environment of care for nursing homes.  
In [42], [PERSON] et al. reviewed smart wearable devices such as fitbit and smart watches in their applications of fitness. They focused on the underlying technologies that power these devices, including both hardware such as sensors and software platforms. They also outlined future research directions.  
In [43], [PERSON] et al. developed an adaptive energy efficient data transmission scheme to minimize power consumption when using wearable devices to collect health and fitness information. The key idea is to consider the physical activities that the user is engaged in while the data are collected. The recognition of the physical activities would put the data in the right context for analysis. When the user is engaged in certain activities and the physiological signal level (such as heart rate) are normal in the context of the activity, the transmission could be omitted, which reduces the transmission rate.  
In [44], [PERSON] et al. proposed a set of algorithms to generate 3D heart models for display in the holography and mixed reality environments. Their algorithms were tested with Microsoft HoloLens, which provides a holographic mix reality display. In [45], [PERSON] and [PERSON] presented a cyber-physical system based on wearable devices for taking physiological and activity data. The system was designed for individuals with diabetes to better quantify the effects of their exercise and activity and understand the positive impact of exercises towards diabetes management.  
In [46], [PERSON] et al. introduced a framework to help develop user-centered smart environments, which consist of various smart devices and interface modalities. At the core of the framework are a digital agent that processes data and provide an adaptive user interface, and a device interface that allow access to context data of smart environments.  
In [47], [PERSON] and [PERSON] reported a design of a speech recognition system that works on wake-up-word, or in the general automatic speech recognition mode. This line of research is important because voice recognition is essential for any smart environment that aims to dynamically interact with one or more users.