OUCH: Objective, Uniform, Controlled Haptic Stimulation for Automated Neurological Assessment
Authors: Sherry Choi, Sitao Sunny Li, Joseph Romero, Lillian Chin, Ashwin G. Ramayya, Allison M. Okamura, Ava Chen
Organizations: Department of Mechanical Engineering, Stanford University, Stanford, CA, USA. · Department of Mechanical Engineering, Rice University, Houston, TX, USA. · Department of Electrical and Computer Engineering, University of Texas at Austin, TX, USA. · Department of Neurosurgery, Stanford University, Stanford, CA, USA.
Motor responses evoked by noxious stimulation are used to assess neurological function in hospitalized patients with disorders of consciousness. In standard bedside assessments, these stimuli are applied manually, resulting in substantial variation in force, duration, frequency, and location. Here, we present OUCH (Objective, Uniform, Controlled Haptic stimulation), a wrist-worn device that uses pneumatic actuation to deliver noxious mechanical stimuli. OUCH combines stacked pneumatic pouch actuators, a rigid indenter, and a compliant spacer designed to buckle at a set load, so that the indenter contacts the skin only during actuation. We characterize the device using blocked force tests, clinician evaluation, finite element analysis, and a deformable pressure testbed, and benchmark it against a commercially available handheld pressure algometer. At 200 kPa pouch inflation pressure, our indenter concentrated its load into an estimated contact pressure of 18,500 kPa, over 25 times that of the algometer tip, while requiring less total force. On the deformable testbed, it localized deformation near the surface, while deformation at depth remained comparable to the algometer. As a result, in preliminary perceptual testing, our indenter elicited discomfort at approximately 89% lower applied force than the algometer, demonstrating the feasibility of evoking discomfort with a compact, wearable soft actuator. These results show that combining pneumatic actuation with designed contact geometry enables controlled, repeatable noxious stimulation at the wrist, providing a foundation for objective neurological assessment.
Figures & tables
Fig. 1 : OUCH wearable device and operating principle. (a) Side view and (b) front view of OUCH on the wrist. (c) Schematic of the device at rest and during neurological assessment, where pneumatic pouch actuator expansion deforms the compliant spacer and drives the indenter into contact with the skin while the IMU tracks motion.
Fig. 2 : Pouch design and blocked force characterization. (a) Exploded view of the blocked force test setup. (b) Pneumatic pouch actuator design iterations with increasing numbers of folds. (c) Finalized stacked 2 × 1 single-layer pouch configuration shown without the OUCH indenter (pouch only; top) and with the OUCH indenter attached beneath the pouch stack (bottom). (d) Blocked force comparison of the pouch designs shown in (b). (e) Blocked force comparison of the finalized pouch configuration with and without the OUCH indenter
Condition
Representative Quotes
Perceived Sensation
Pouch Only
“It doesn’t hurt me.” “Feels like I’ve overtightened the watch strap.”
Broad pressure sensation without pain.
Pouch with OUCH Indenter
“Oh now it’s starting to hurt.” “This is perfect.” “This is good, I like it.”
Noticeable discomfort at an appropriate intensity.
TABLE I : Representative clinician feedback comparing the pneumatic pouch actuator alone and the pouch with the OUCH indenter.
Fig. 3 : Compliant spacer design and characterization. (a) Measured force-displacement response during compression of the spacer, with numbered points corresponding to selected deformation states. (b) Comparison of spacer deformation during manual compression testing and finite element analysis (FEA) at the corresponding applied forces. Asterisk (second) state is the buckling point.
Fig. 4 : Deformable pressure testbed setup. (a) Photo of the experimental setup of OUCH wrapped around the deformable pressure testbed, with blue and orange markers indicating top and bottom sensor locations, respectively. (b) Schematic of the deformable pressure testbed, with blue and orange indicating sensor channels for the top and bottom sensors, respectively, and the differential pressure-sensing mechanism used to quantify local pressure changes.
Fig. 5 : Deformable pressure testbed characterization. (a) Pouch inflation pressure profile over time during stepwise loading. (b) Testbed sensor readings from the top and bottom sensing channels on the deformable testbed indicated in Fig. 4 for the AlgoMed and OUCH indenters under the inflation pressure profile in (a). (c) Representative photos of testbed deformation with the AlgoMed and OUCH indenters under pouch inflation pressures of 120, 160, and 200 kPa. Scale bars represent 10 mm.
Fig. 6 : FEA characterization on the deformable testbed. Cross-sectional FEA results showing spacer deformation and indenter engagement with increasing applied displacement U . (a) FEA model of the compliant spacer, OUCH indenter, and deformable pressure testbed. (b) Spacer buckling before contact ( U=2.83 mm). (c) Initial contact ( U=3.02 mm; peak contact pressure 1,240 kPa). (d) Maximum peak contact pressure ( U=5.98 mm; 11,350 kPa). (e) Expanded contact ( U=6.70 mm; 4,280 kPa). (f) Loading state corresponding to the 200 kPa testbed condition ( U=8.94 mm; indentation 5.94 mm; 5,010 kPa).
Fig. 7 : Comparison of the AlgoMed tip and OUCH indenter. (a) Blocked force measurements comparing force output as a function of applied pressure. (b) Calculated contact pressure on a logarithmic scale using the measured forces in (a) and the respective contact areas of 78.5 mm 2 for the AlgoMed tip and 2.27 mm 2 for the OUCH indenter, with labels indicating pressure differences between the two tips. (c) Applied force at the reported discomfort threshold from four research team members using the AlgoMed tip and OUCH indenter.
Soft, wearable robotic devices can deliver haptic feedback to support a wide range of tasks, such as extended reality, training various skills, and rehabilitation. Pneumatic actuation can deliver complex haptic feedback, is lightweight and compliant, and can be incorporated into textiles, making it promising for wearable applications. These soft pneumatic devices, however, typically require a valve and input for each pneumatic actuator, making it challenging to develop fully portable devices for at-home use. In this work we present a pneumatic unit for logic-based sequential excitation (PULSE). The PULSE is a flat, textile-based pneumatic actuator with embedded fluidic logic. By combining these actuators into a fluidic ring oscillator, we decreased the typical amount of required pneumatic inputs for a haptic forearm sleeve by 60%, with the ability to scale. We built the ring oscillator by optimizing design variables to reach desired periods of oscillation. We demonstrated a set of tactile stroking cues with periods ranging from 1.16 to 1.56 s and forces ranging from 1.07 to 2.04 N. We assessed the sleeve's ability to render differentiable, pleasant, and continuous haptic cues in a user study. The forearm sleeve containing PULSEs successfully delivered four directional cues and guided users to target wrist angles with fast reaction times, low overshoot amounts, and a 93.3% average accuracy of correct initial directions.
Jessica Healey, Anoush Sepehri, Michael T. Tolley +1
University of California, San Diego, La Jolla CA 92093, USA
We present a system of two wearable pneumatic haptic devices that supports continuous, closed-loop, bidirectional tactile interaction at perceptually relevant force and temporal scales. A single device can contain up to twelve pressure sensing channels connected to textile-based pneumatic pouches. Each channel in a device can be used as a sensor, an actuator, or both. As an actuator with integrated sensing, the channel generates stable skin indentation through local closed-loop control. As a sensor, a channel can be mounted (or worn) on any surface, including on a robot gripper or on the human body, and used to measure touch interactions with the environment or a human user. A distributed architecture supports sustained pressure output, rapid dynamic response, and wireless pairing of identical devices in a system to transmit and reproduce tactile pressure signals in real time. Device-level characterization demonstrates force bandwidth exceeding 30 Hz, rapid and well-damped step responses, and extended pressure retention compared to prior compact pneumatic platforms. Human studies show that pressure-based fingertip feedback enables discrimination of force and stiffness, improves teleoperated manipulation by reducing applied pressures by up to 23.1% and task duration by up to 27.4%, and lowers subjective mental workload by 18.8%, particularly under visually constrained conditions. By unifying tactile sensing and haptic feedback within a single pneumatic modality, the device provides a practical foundation for bidirectional touch interaction in teleoperation.
Cosima du Pasquier, Aliyah Smith, Serin Huber +5
Department of Mechanical Engineering, Stanford University, Stanford, CA, USA
Object manipulation is fundamental to virtual reality (VR) applications, yet conventional fingertip haptic devices fail to render certain tactile features relevant for immersive and precise interactions, as i.e. detection of edges. This paper presents a compact, lightweight fingertip haptic device (24.3 g) that delivers distinguishable surface and edge contact feedback through a novel dual-motor mechanism. Pressure distribution characterization using a 6 x 6 flexible sensor array demonstrates distinct contact patterns between the two stimulation modes. A preliminary user study with five participants achieved 93% average classification accuracy across four conditions (edge/surface contact with light/heavy pressure), with mean response times of 2.79 seconds. The results indicate that the proposed device can effectively convey edge and surface tactile cues, potentially enhancing object manipulation fidelity in VR environments.
Rui Chen, Xianlong Mai, Alireza Sanaei +3
Institute of Mechanical Intelligence, School of Advanced Studies Sant’Anna (SSSA), 56127 Pisa, Italy. · CAS Key Laboratory of Mechanical Behavior and Design of Materials, Institute of Humanoid Robots, School of Engineering Sciences, University of Science and Technology of China, Hefei, China.