Quantifying Real-Time Complex Force Dynamics in Force-Based Manipulation Using Newly Developed Soft Wearable Electronic Skin

About This Grant

Project Summary/Abstract Force-based manipulation (FBM) or manual therapy (e.g., spinal mobilization, spinal manipulation, massage) have proven moderately effective for treating musculoskeletal pain (e.g., low back pain) and are currently recommended by most clinical guidelines as a first-line conservative treatment approach. However, for decades, the lack of FBM delivery standardization and the persistence of mechanism-related knowledge gaps have prevented the therapeutic optimization of FBM. Moreover, considerable heterogeneity in force/pressure dynamics exists during manual delivery between different FBM clinicians, which remains a significant barrier to comparing FBM-related clinical trial results. Indeed, very few imperceptible force/pressure-sensing technologies are available that allow FBM clinicians to quantify mechanical dynamics in high spatiotemporal resolution without tactile interference during FBM delivery, largely due to the grand challenges associated with developing such technologies at the material, manufacturing, and system levels. In our preliminary study, we developed a digital manufacturing process for producing large-scale, soft, pressure-sensing e-skins, featuring highly customizable designs, quick turnarounds, and low costs. Through programmable microstructural engineering, the resulting soft e-skins exhibited exceptional sensing performance, including a broad dynamic range (>560 kPa), rapid response (millisecond-level), high sensitivity (single hair weight detection), and low hysteresis (<5%). When integrated on the hand, we demonstrated that a 256-pixel full-hand e-skin readily enabled large-scale spatiotemporal data collection for complex human grasp analysis. In this R21 project, we aim to modify our personalizable e-skins for real-time quantification of complex mechanical dynamics during FBM, while minimizing tactile interference for clinicians and maximize their FBM delivery performance. In Aim 1, we will design, fabricate, and characterize soft, wearable, pressuring-sensing e-skins tailored for FBM, with their performance and accuracy benchmarked against off-the-shelf sensors. In Aim 2, we will calibrate, optimize, and extend the use of e-skins for measuring complex pressure dynamics during FBM directly at the clinician-patient interface. 12 licensed manual therapy clinicians will wear personalized e-skins and deliver three distinct types of FBM techniques to 12 asymptomatic human participants. Both quantitative pressure dynamics (i.e., peak pressure magnitude, time-to-peak, contact area, duration, spatiotemporal sequence) and qualitative clinician feedback will be collected and statistically analyzed. Once demonstrated as efficacious, this work has the potential to transform the FBM field by providing a long-desired toolkit for quantitative research, which cannot be achieved with existing technologies. It will also open opportunities for standardizing FBM delivery, optimizing prescriptive dosage, and correlating specific force/pressure application characteristics with downstream chemical, physiological, and therapeutic outcomes.