Smart Device Development for Gait Monitoring: Multimodal Feedback in an Interactive Foot Orthosis, Walking Aid, and Mobile Application

Smart assistive technologies such as sensor-based footwear and walking aids offer promising opportunities for gait rehabilitation through real-time feedback and patient-centered monitoring. While biofeedback applications show great potential, current research rarely explores integrated closed-loop systems with device- and modality-specific feedback. In this work, we present a modular sensor-based system combining a smart foot orthosis and an instrumented forearm crutch to deliver real-time vibrotactile biofeedback. The system integrates plantar pressure and motion sensing, vibrotactile feedback, and wireless communication via a smartphone application. We conducted a user study with eight participants to validate the system’s feasibility for mobile gait detection and app usability, and to evaluate different vibrotactile feedback types across the orthosis and forearm crutch. The results indicate that pattern-based vibrotactile feedback was rated as more useful and suitable for regular use than simple vibration alerts. Moreover, participants reported clear perceptual differences between feedback delivered via the orthosis and the forearm crutch, indicating device-dependent feedback perception. The findings highlight the relevance of feedback strategy design beyond hardware implementation and inform the development of user-centered haptic biofeedback systems.

💡 Research Summary

This paper presents the development and evaluation of an integrated, modular smart system designed for gait rehabilitation and monitoring. The research addresses a gap in current assistive technology, which often lacks closed-loop systems capable of providing real-time, device-specific biofeedback. The proposed system synergistically combines three components: a Smart Foot Orthosis (SFO) equipped with inertial measurement units (IMUs) and force-sensing resistors (FSRs) for plantar pressure and motion detection, an instrumented forearm crutch with its own IMU and haptic actuators, and a smartphone application for data processing, visualization, and feedback control.

The study follows a structured validation approach. First, it establishes foundational feasibility by comparing the SFO’s gait event detection accuracy against a clinical-grade instrumented treadmill (Zebris), achieving a high mean accuracy of 97.5% (SRQ1). The usability of the companion mobile app was also assessed using the System Usability Scale (SUS), yielding a “good” average score of 77.8 from participants (SRQ2). These initial validations ensured the system’s reliability for the core investigation.

The primary research focus (MRQ) was to evaluate user perception of different vibrotactile feedback strategies delivered through the orthosis and the crutch. In a user study with eight healthy participants, two feedback types were tested: simple continuous vibration and more complex pattern-based vibration (using intervals and intensity variations). Subjective ratings were collected on noticeability, intrusiveness, perceived usefulness, and intention for regular use.

The key findings are twofold. First, regarding feedback type, pattern-based vibrotactile feedback was consistently and significantly rated as more useful, less intrusive, and more suitable for regular use than simple continuous vibration alerts. This suggests that the informational design of the feedback signal itself is critical for user acceptance and perceived effectiveness. Second, regarding feedback location, participants reported clear perceptual differences between feedback delivered via the foot orthosis versus the forearm crutch. This indicates that the point of contact on the body (foot vs. hand) influences how the feedback is sensed and interpreted, a phenomenon described as device-dependent feedback perception.

The paper concludes that the development of user-centered haptic biofeedback systems must extend beyond hardware integration and sensor accuracy. The design of the feedback strategy—including its temporal pattern, rhythm, and the careful selection of the delivery device based on the target user’s condition and sensory perception—is paramount for creating effective and acceptable rehabilitative interventions. This work provides empirical evidence and practical design insights for advancing interactive assistive technologies in human-computer interaction (HCI) and rehabilitation engineering.