Wearable Technology at the Point-of-Care

Stay connected



Share on facebook
Share on twitter
Share on linkedin

CIS Colloquium, Dec 12, 2007, 03:30PM – 04:30PM, TECH Center 111

Wearable Technology at the Point-of-Care

Dr. Paolo Bonato, Department of Physical Medicine and Rehabilitation, Harvard Medical School The Harvard-MIT Division of Health Sciences and Technology

Significant progress in computer technologies, solid-state micro sensors, and telecommunication has advanced the possibilities for individual health monitoring systems. A variety of compact, unobtrusive sensors are available today and it is expected that more will be available in the near future. This talk will discuss this rapidly evolving technology and how to use it in order to develop wearable systems to monitor patients undergoing rehabilitation. System configurations consisting of wireless miniature sensors or a sensor suit that relies on e-textile solutions will be presented in the perspective of using such tools to measure motor functions and systemic responses during the accomplishment of motor activities. Measuring motor functions and associated systemic responses is key in physical medicine and rehabilitation to effectively plan and adapt clinical interventions as a function of the observed response on a patient-by-patient basis.

Data collection and storing are key elements of these systems. Wearable systems often rely on PDA’s and similar data-logging devices, i.e. means to temporarily store physiological signals before uploading them to a server located in a clinical center. Data uploading may occur via a wireless local network installed in the inpatient unit or the patient’s home, which allows communication with a clinical server via an access point. Alternatively, cell phone technology can be used when immediate access to the clinical data is an important consideration of the system design.

Data processing and analysis will be discussed as a key issue to make progress toward the clinical application of wearable systems. Procedures can rely on advanced signal processing and data mining methods to identify features of the recorded data that capture the desired clinical information. Development of data processing and analysis procedures will be discussed in the context of integrating laboratory and clinical assessments with data gathered in the field for the purpose of designing clinical interventions aimed at enhancing mobility in individuals with cardio-pulmonary, musculo-skeletal, and/or neurological conditions. Three examples will be shortly discussed: predicting exacerbation episodes in subjects with chronic obstructive pulmonary disease undergoing pulmonary rehabilitation, adjusting medications in patients with late stage Parkinson’s disease, and enhancing gait retraining in post-stroke individuals via next generation wearable robotic devices.

Through development of innovative, reliable, and unobtrusive means to monitor the health status of individuals in the field, researchers are expected to provide clinicians with information complementary to that typically gathered in clinical settings. This would enable clinicians to more precisely tailor their rehabilitative strategies to the daily lifestyle of the patient, and to remotely track and quantify the patient’s progression toward recovery.