Background Literature
Digital health technologies such as smartphones and wearable devices have vastly expanded the foundation for supporting robust, mobile, home-based rehabilitation to augment outpatient therapy. The support of therapeutic activities via mobile devices has been referred to as mobile rehabilitation or “mRehab.” The Rehabilitation Engineering Research Center on Mobile Rehabilitation (mRehab RERC) was established ito advance the field through technology development and research demonstrating the value of mRehab solutions. The “State of the Science” (SOS) conference will describe the current state of technology and needs for future research and development. The conference will include invited presentations followed by an interactive workshop with presenters and attendees to identity and prioritize needs for future research and development. Four topic areas will be addressed: 1) effectiveness of home exercise; 2) technology for remote monitoring and support; 3) use of “Big Data” to promote therapy adherence, and 4) barriers and facilitators to adoption of mRehab.
Learning Objectives:
Adherence to and effectiveness of home/remote therapeutic exercise • Understand patterns of home exercise adherence and projected patient improvement outcomes. • Identify barriers to adherence in home exercise programs as well as interventions to address these barriers. • Provide examples of strategies used to increase inclusiveness when developing mRehab interventions. • Provide insights into mRehab development--the importance of user-centered content, design and features.
Technology for remote monitoring and support • Identify clinical benefits and recommended design features for simple sensor systems to measure and motivate home exercise. • Describe a framework to guide the selection and design of chatbot-delivered rehabilitation interventions. • Identify preliminary evidence that Chatbots may be usable and promote adherence. • Identify necessary next steps to integrate wearable technology into clinical practice.
Analytic techniques for managing “Big Data” available from mRehab • Distinguish between approaches to developing automated coaching programs: behavioral/psychological theory and machine learning. • Explain the process for incorporating both behavioral/psychological theory and machine learning in an automated coaching program.
Barriers and facilitators to uptake and adoption of mRehab • Identify opportunities and limitations for implementation of remote physiologic/therapeutic monitoring (RPM/RTM) under current reimbursement policies. • Understand how economic, business, social and technological trends will shape public policy related to FDA review, insurance reimbursement and information security for innovative technologies to support RPM/RTM. • Describe primary barriers and benefits to implementing an mRehab system in an outpatient clinic.