Big Data Analytics and Sensor-Enhanced Activity Management to Improve Effectiveness and Efficiency of Outpatient Medical Rehabilitation

Abstract

Numerous societal trends are compelling a transition from inpatient to outpatient venues of care for medical rehabilitation. While there are advantages to outpatient rehabilitation (e.g., lower cost, more relevant to home and community function), there are also challenges including lack of information about how patient progress observed in the outpatient clinic translates into improved functional performance at home. At present, outpatient providers must rely on patient-reported information about functional progress (or lack thereof) at home and in the community. Information and communication technologies (ICT) offer another option—data collected about the patient’s adherence, performance and progress made on home exercises could be used to help guide course corrections between clinic visits, enhancing effectiveness and efficiency of outpatient care. In this article, we describe our efforts to explore use of sensor-enhanced home exercise and big data analytics in medical rehabilitation. The goal of this work is to demonstrate how sensor-enhanced exercise can improve rehabilitation outcomes for patients with significant neurological impairment (e.g., from stroke, traumatic brain injury, and spinal cord injury). We provide an overview of big data analysis and explain how it may be used to optimize outpatient rehabilitation, creating a more efficient model of care. We describe our planned development efforts to build advanced analytic tools to guide home-based rehabilitation and our proposed randomized trial to evaluate effectiveness and implementation of this approach.

Impairment and Compensation in Dexterous Upper-Limb Function After Stroke. From the Direct Consequences of Pyramidal Tract Lesions to Behavioral Involvement of Both Upper-Limbs in Daily Activities

“…Many technologies, wearable or not (neurotechnologies, virtual reality, robotics, games, telerehabilitation etc.) are being developed in order to increase the intensity and duration of therapeutic activities in the home environment ( Dobkin, 2017 ; Maceira-Elvira et al, 2019 ; Jones et al, 2020 ). Whilst the description of technology assisted rehabilitation methods is beyond the scope of the present article, it is worthy to note that continued fitness exercises as part of home rehabilitation programs are crucial for maintaining and improving motor functioning of both upper limbs in the long term ( Ward et al, 2019 ).…”

“…Activity and independence might conversely be investigated in the patient’s natural environment (home or supported care) where daily life gestures would be facilitated (or impeded) by the physical organization and supports available in those surrounds. The increasing sophistication of technological aids (sensors, wearable devices, and home automation) available for use in the home represent an important means for expanding knowledge on patient movements and strategies and for prolonged rehabilitation in the home ( Dobkin, 2017 ; Maceira-Elvira et al, 2019 ; Jones et al, 2020 ). While the majority of consumer wearables are focused are focused on tracking some vital signs (heart rhythms and body temperature) or global activity level, extensive research is currently being conducted on the development of wearable systems relying on different technologies (accelerometers, Inertial Measurement Units-IMUs, wearable robotics or EMG sensors) for monitoring and providing feedback on upper body posture and upper-limbs movements ( Wang et al, 2017 ).…”

Using Large-Scale Sensor Data to Test Factors Predictive of Perseverance in Home Movement Rehabilitation: Optimal Challenge and Steady Engagement

“…It is also feasible to quantify the exact amount of exercise associated with generating a therapeutic benefit on movement capability, which would help settle an open, fundamental question in rehabilitation practice ( 49 , 50 ). Using artificial intelligence to predict dropout and to automatically send encouragements or adapt system parameters is an interesting possibility ( 51 ). Finally, an important direction for future research is to study the “super-users” who persevered the most to try to determine what factors contributed to their extreme behavior.…”

Orientation of the Head and Trunk During Functional Upper Limb Movement

“…Ultimately, this work should be extended to the analysis of more complex arm movements (e.g., in the context of sporting activities) in order to examine patterns of coordination across the head, neck, trunk and upper limb with the perspective of both preventing injury and enhancing athletic performance [63,64]. In particular, wearable sensor technology [65][66][67][68] could be used to detect inefficient or unsafe coordination patterns during ballistic arm movements (e.g., striking, throwing) under more ecological conditions (e.g., volleyball, American football). In the same idea, this may pave the road for innovative solutions using online feedback to assist with correcting issues such as rigid coupling or inefficient timing of counter-rotation through the cervical spine.…”