The privacy-aware compliance tracking system

The privacy-aware compliance tracking system (PACTS) is designed for both training of state tested nurse aids (STNAs) on using proper body mechanics while doing bedside care activities, and provide real-time monitoring and feedback while STNAs are taking care of residents at the bedside. Each PACTS consists of a laptop/desktop computer, a Microsoft Kinect sensor, one or more smart phones, and one or more smart wearable devices (such as smart watches and programmable wearable trackers). The system ensures that only consented STNAs are tracked, hence the privacy of other persons that might be in the view of the Kinect sensor is protected. Improper activities that might increase the risk of lower back pains will be detected by the system and the event will be recorded. An STNA can view her performance both on her smart wearable device, or on her smart phone, both via a proprietary app that comes with the system. A separate application is made available to authorized administrators’ of an institution to view the overall cumulative statistics on the performance of STNAs working at the institution.

A user of the system is required to wear a pre-configured smart watch, and be aware of the placement of the Kinect sensor so that she/he could stand in front of Kinect to register with our system by making a predefined gesture. An alert in the form a vibration and a message display at the wearable device is delivered to the user whenever the system has detected that the user has done an improper activity as defined by the system.

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System Architecture for a Single PACTS

Multi-Room Systems

System Architecture for Multi-Room Deployment



A consented STNA will wear a Pebble smart watch on her/his wrist. The user will need to register with the Kinect server by pushing the select button of the watch while making a pre-defined gesture. This serves for two purposes: (1) we ensure only the consented STNA is tracked, and (2) the system identifies the user and stores the detected activities accordingly. On detecting a wrong activity, such as a sever bending, a record is stored in a local log file. The following is an example log. The log protect the user's privacy and the logged information cannot be used to infer any information (such as whether or not a abuse action has occurred) other than the pre-defined activities.

sample log
Activities

Bedside Activities

We have experimented many bedside activities as shown above. On the left is a simulated study in an actual resident room at Jennings. On the right is a study at the Jennings Fall Frenzy competence tracking where an STNA tried out our system.

Publications

  1. Zhao, Wenbing, Roanna Lun, Connor Gordon, Abou-Bakar M. Fofana, Deborah D. Espy, M. Ann Reinthal, Beth Ekelman, Glenn D. Goodman, Joan E. Niederriter, and Xiong Luo. "A Human-Centered Activity Tracking System: Toward a Healthier Workplace." IEEE Transactions on Human-Machine Systems (2017). (in vitro testing)
  2. Zhao, Wenbing, Roanna Lun, Connor Gordon, Abou-Bakar M. Fofana, Deborah D. Espy, Ann Reinthal, Beth Ekelman et al. "LiftingDoneRight: A Privacy-Aware Human Motion Tracking System for Healthcare Professionals." International Journal of Handheld Computing Research (IJHCR) 7, no. 3 (2016): 1-15. (development)
  3. Zhao, W., Wu, Q., Padaraju, V., Bbela, M., Reinthal, M. A., Espy, D. D., Luo, X., & Qiu, T. (2017, October). A Privacy-Aware Compliance Tracking System for Skilled Nursing Facilities, In Systems, Man, and Cybernetics (SMC), 2017 IEEE International Conference on (accepted). IEEE. (development and in vivo testing)
  4. Zhao, W., Wu, Q., M., Reinthal, M. A., Espy, D. D., Luo, X., & Qiu, T. (2017, October). Enhancing Body Mechanics Training for Bedside Care Activities with a Kinect-Based System, In Systems, Man, and Cybernetics (SMC), 2017 IEEE International Conference on (accepted). IEEE. (training)
  5. Zhao, Wenbing, Qing Wu, Deborah D. Espy, M. Ann Reinthal, Beth Ekelman et al. ".A Feasibility Study on Using a Low-Cost Nonintrusive Human Motion Tracking System to Promote Safe Patient Handling" In Electro Information Technology (EIT), 2017 IEEE International Conference on, pp. 462-466. IEEE, 2017. (in vivo testing)
  6. Zhao, Wenbing, Roanna Lun, Connor Gordon, Abou-Bakar Fofana, Deborah D. Espy, M. Ann Reinthal, Beth Ekelman et al. "A privacy-aware Kinect-based system for healthcare professionals." In Electro Information Technology (EIT), 2016 IEEE International Conference on, pp. 0205-0210. IEEE, 2016. (development)
  7. Zhao, Wenbing, Deborah D. Deborah, M. Ann Reinthal, Beth Ekelman, Glenn Goodman, and Joan Niederriter. "Privacy-aware human motion tracking with realtime haptic feedback." In Mobile Services (MS), 2015 IEEE International Conference on, pp. 446-453. IEEE, 2015. (development)

Disclaimer

PACTS uses a patent pending technology owned by Cleveland State University. Interested parties should contact Dr. Wenbing Zhao for possible licensing agreement.