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C11 VISUAL ARTS
C11 VISUAL ARTS
C11 VISUAL ARTS
TACTICLE Memory RECALL



A Haptic Interface for Embodied Spatial Recall
A Haptic Interface for Embodied Spatial Recall
A Haptic Interface for Embodied Spatial Recall
Abstract
Tactile Memory Recall is a low-cost haptic interface that encodes and retrieves spatial memories through embodied finger poses and vibrotactile feedback. Rather than relying on visual or auditory cues, the system uses proprioception as the primary channel of recall. It records finger pose configurations using three IMUs, stores them in persistent memory, and triggers localized haptic feedback when users reproduce the stored poses. By grounding memory formation in sensorimotor experience, the system advances embodied cognition approaches to spatial memory augmentation and accessibility.
Keywords: haptics, embodied cognition, proprioception, tangible interfaces, wearable computing, tactile memory, memory augmentation
1. Motivation & Contribution
Existing memory augmentation tools privilege vision and sound, despite decades of evidence that touch and proprioception are crucial in forming and retrieving spatial memories (e.g., Varela et al. 1991; O’Keefe & Nadel 1978). This project proposes an alternative approach: memory is not shown but felt.
Key Contributions
Embodied memory encoding and retrieval via natural finger poses.
Low-cost, open-source hardware design ($137) that supports replication.
Real-time haptic feedback (<50 ms latency) mapped directly to finger pose similarity.
Evaluation framework for measuring tactile recall accuracy, interference, and retention.
2. System Overview
MAP Mode — Encoding
User presses against an object (force > 150 units).
Finger pose orientation (thumb, index, middle) is recorded for 3 s.
The system averages readings and stores them in EEPROM (5-slot capacity).
REPLAY Mode — Retrieval
User moves fingers through space.
Real-time pose data is compared with stored vectors using Euclidean distance.
When distance < 300°, all vibration motors activate at maximum intensity, signaling a match.
Latency: <50 ms end-to-end at 100 Hz loop frequency.
3. Technical Architecture
Hardware rationale
IMU: pose sensing with 6-DOF precision.
Multiplexer: allows multiple IMUs on one bus.
FSRs: trigger intentional memory recording.
Coin motors: provide direct tactile feedback.
Software
Finite state machine with modes:
IDLE,MAP,REPLAY,CALIBRATE.Serial commands for debugging and control.
Tolerance-based matching prioritizes perception over precision.
4. Bill of Materials (BOM)
Component | Model | Qty | Cost | Purpose |
|---|---|---|---|---|
Microcontroller | Arduino Mega 2560 | 1 | $45 | Main processing unit |
I2C Multiplexer | TCA9548A | 1 | $8 | Multi-IMU communication |
IMU Sensors | MPU6050 | 3 | $15 | Pose tracking |
Force Sensors | FSR 402 | 3 | $36 | Contact detection |
Vibration Motors | 10 mm coin motors | 3 | $12 | Haptic feedback |
MOSFETs + Resistors | 2N7000 + 1k/10kΩ | 6 | $3.50 | Motor control & biasing |
Breadboard & Wires | — | — | $17 | Assembly |
Total Cost | $137 |
5. Research Context & Motivation
Theoretical Framework
Enactive Cognition: knowledge arises through dynamic interaction (Varela et al., 1991).
Motor-Sensory Integration: movement shapes perception and memory.
Situated Learning: memory is tied to spatial context.
Spatial Memory Research
Cognitive maps (O’Keefe & Nadel 1978) integrate multisensory input.
Haptic exploration enhances retention (Lederman & Klatzky 1987, 2009).
Research Gaps
Visual/auditory bias in memory tools.
Lack of embodied, sensorimotor interfaces.
Accessibility limitations for visually impaired users.
Contribution Tactile Memory Recall provides proprioceptive encoding, natural gesture-based retrieval, and inclusive design beyond visual channels.
6. Future Work
Wireless ESP32 integration for untethered wearability.
Miniaturized ring-form factor sensors.
Richer haptic modalities (directional, thermal, ultrasonic).
Adaptive ML-based thresholds and personalization.
Integration with assistive navigation and spatial learning applications.
7. Ethics & Accessibility
Haptic intensity capped to safe tactile levels.
No personal data stored; only numeric pose vectors.
Supports private, silent recall — valuable for visually impaired users.
8. References
Varela, F. J., Thompson, E., & Rosch, E. (1991). The embodied mind. MIT Press.
Clark, A. (1997). Being There. MIT Press.
O’Keefe, J., & Nadel, L. (1978). The hippocampus as a cognitive map. OUP.
Lederman, S. J., & Klatzky, R. L. (1987, 2009). Haptic perception.
Dourish, P. (2001). Where the Action Is. MIT Press.
Brock, A. M. et al. (2015). Human–Computer Interaction, 30(2).
Yates, F. A. (1966). The Art of Memory.
Legge, E. L. et al. (2012). Acta Psychologica.
Pearce, J. M. (2012). Science.
Nosek, B. A. et al. (2015). Science.
9. Citation
Project page: https://www.c11visualarts.com/altered-perception---tactile-memory-recall
GitHub repository: https://github.com/CJD-11/Tacticle-Memory-Recal
Abstract
Tactile Recall is a low-cost haptic interface that encodes and retrieves spatial memories through embodied finger poses and vibrotactile feedback. Rather than relying on visual or auditory cues, the system uses proprioception as the primary channel of recall. It records finger pose configurations using three IMUs, stores them in persistent memory, and triggers localized haptic feedback when users reproduce the stored poses. By grounding memory formation in sensorimotor experience, the system advances embodied cognition approaches to spatial memory augmentation and accessibility.
Keywords: haptics, embodied cognition, proprioception, tangible interfaces, wearable computing, tactile memory, memory augmentation
1. Motivation & Contribution
Existing memory augmentation tools privilege vision and sound, despite decades of evidence that touch and proprioception are crucial in forming and retrieving spatial memories (e.g., Varela et al. 1991; O’Keefe & Nadel 1978). This project proposes an alternative approach: memory is not shown but felt.
Key Contributions
Embodied memory encoding and retrieval via natural finger poses.
Low-cost, open-source hardware design ($137) that supports replication.
Real-time haptic feedback (<50 ms latency) mapped directly to finger pose similarity.
Evaluation framework for measuring tactile recall accuracy, interference, and retention.
2. System Overview
MAP Mode — Encoding
User presses against an object (force > 150 units).
Finger pose orientation (thumb, index, middle) is recorded for 3 s.
The system averages readings and stores them in EEPROM (5-slot capacity).
REPLAY Mode — Retrieval
User moves fingers through space.
Real-time pose data is compared with stored vectors using Euclidean distance.
When distance < 300°, all vibration motors activate at maximum intensity, signaling a match.
Latency: <50 ms end-to-end at 100 Hz loop frequency.
3. Technical Architecture
Hardware rationale
IMU: pose sensing with 6-DOF precision.
Multiplexer: allows multiple IMUs on one bus.
FSRs: trigger intentional memory recording.
Coin motors: provide direct tactile feedback.
Software
Finite state machine with modes:
IDLE,MAP,REPLAY,CALIBRATE.Serial commands for debugging and control.
Tolerance-based matching prioritizes perception over precision.
4. Bill of Materials (BOM)
Component | Model | Qty | Cost | Purpose |
|---|---|---|---|---|
Microcontroller | Arduino Mega 2560 | 1 | $45 | Main processing unit |
I2C Multiplexer | TCA9548A | 1 | $8 | Multi-IMU communication |
IMU Sensors | MPU6050 | 3 | $15 | Pose tracking |
Force Sensors | FSR 402 | 3 | $36 | Contact detection |
Vibration Motors | 10 mm coin motors | 3 | $12 | Haptic feedback |
MOSFETs + Resistors | 2N7000 + 1k/10kΩ | 6 | $3.50 | Motor control & biasing |
Breadboard & Wires | — | — | $17 | Assembly |
Total Cost | $137 |
5. Research Context & Motivation
Theoretical Framework
Enactive Cognition: knowledge arises through dynamic interaction (Varela et al., 1991).
Motor-Sensory Integration: movement shapes perception and memory.
Situated Learning: memory is tied to spatial context.
Spatial Memory Research
Cognitive maps (O’Keefe & Nadel 1978) integrate multisensory input.
Haptic exploration enhances retention (Lederman & Klatzky 1987, 2009).
Research Gaps
Visual/auditory bias in memory tools.
Lack of embodied, sensorimotor interfaces.
Accessibility limitations for visually impaired users.
Contribution Tactile Memory Recall provides proprioceptive encoding, natural gesture-based retrieval, and inclusive design beyond visual channels.
6. Future Work
Wireless ESP32 integration for untethered wearability.
Miniaturized ring-form factor sensors.
Richer haptic modalities (directional, thermal, ultrasonic).
Adaptive ML-based thresholds and personalization.
Integration with assistive navigation and spatial learning applications.
7. Ethics & Accessibility
Haptic intensity capped to safe tactile levels.
No personal data stored; only numeric pose vectors.
Supports private, silent recall — valuable for visually impaired users.
8. References
Varela, F. J., Thompson, E., & Rosch, E. (1991). The embodied mind. MIT Press.
Clark, A. (1997). Being There. MIT Press.
O’Keefe, J., & Nadel, L. (1978). The hippocampus as a cognitive map. OUP.
Lederman, S. J., & Klatzky, R. L. (1987, 2009). Haptic perception.
Dourish, P. (2001). Where the Action Is. MIT Press.
Brock, A. M. et al. (2015). Human–Computer Interaction, 30(2).
Yates, F. A. (1966). The Art of Memory.
Legge, E. L. et al. (2012). Acta Psychologica.
Pearce, J. M. (2012). Science.
Nosek, B. A. et al. (2015). Science.
9. Citation
Project page: https://www.c11visualarts.com/altered-perception---tactile-memory-recall
GitHub repository: https://github.com/CJD-11/Tacticle-Memory-Recal
Abstract
Tactile Recall is a low-cost haptic interface that encodes and retrieves spatial memories through embodied finger poses and vibrotactile feedback. Rather than relying on visual or auditory cues, the system uses proprioception as the primary channel of recall. It records finger pose configurations using three IMUs, stores them in persistent memory, and triggers localized haptic feedback when users reproduce the stored poses. By grounding memory formation in sensorimotor experience, the system advances embodied cognition approaches to spatial memory augmentation and accessibility.
Keywords: haptics, embodied cognition, proprioception, tangible interfaces, wearable computing, tactile memory, memory augmentation
1. Motivation & Contribution
Existing memory augmentation tools privilege vision and sound, despite decades of evidence that touch and proprioception are crucial in forming and retrieving spatial memories (e.g., Varela et al. 1991; O’Keefe & Nadel 1978). This project proposes an alternative approach: memory is not shown but felt.
Key Contributions
Embodied memory encoding and retrieval via natural finger poses.
Low-cost, open-source hardware design ($137) that supports replication.
Real-time haptic feedback (<50 ms latency) mapped directly to finger pose similarity.
Evaluation framework for measuring tactile recall accuracy, interference, and retention.
2. System Overview
MAP Mode — Encoding
User presses against an object (force > 150 units).
Finger pose orientation (thumb, index, middle) is recorded for 3 s.
The system averages readings and stores them in EEPROM (5-slot capacity).
REPLAY Mode — Retrieval
User moves fingers through space.
Real-time pose data is compared with stored vectors using Euclidean distance.
When distance < 300°, all vibration motors activate at maximum intensity, signaling a match.
Latency: <50 ms end-to-end at 100 Hz loop frequency.
3. Technical Architecture
Hardware rationale
IMU: pose sensing with 6-DOF precision.
Multiplexer: allows multiple IMUs on one bus.
FSRs: trigger intentional memory recording.
Coin motors: provide direct tactile feedback.
Software
Finite state machine with modes:
IDLE,MAP,REPLAY,CALIBRATE.Serial commands for debugging and control.
Tolerance-based matching prioritizes perception over precision.
4. Bill of Materials (BOM)
Component | Model | Qty | Cost | Purpose |
|---|---|---|---|---|
Microcontroller | Arduino Mega 2560 | 1 | $45 | Main processing unit |
I2C Multiplexer | TCA9548A | 1 | $8 | Multi-IMU communication |
IMU Sensors | MPU6050 | 3 | $15 | Pose tracking |
Force Sensors | FSR 402 | 3 | $36 | Contact detection |
Vibration Motors | 10 mm coin motors | 3 | $12 | Haptic feedback |
MOSFETs + Resistors | 2N7000 + 1k/10kΩ | 6 | $3.50 | Motor control & biasing |
Breadboard & Wires | — | — | $17 | Assembly |
Total Cost | $137 |
5. Research Context & Motivation
Theoretical Framework
Enactive Cognition: knowledge arises through dynamic interaction (Varela et al., 1991).
Motor-Sensory Integration: movement shapes perception and memory.
Situated Learning: memory is tied to spatial context.
Spatial Memory Research
Cognitive maps (O’Keefe & Nadel 1978) integrate multisensory input.
Haptic exploration enhances retention (Lederman & Klatzky 1987, 2009).
Research Gaps
Visual/auditory bias in memory tools.
Lack of embodied, sensorimotor interfaces.
Accessibility limitations for visually impaired users.
Contribution Tactile Memory Recall provides proprioceptive encoding, natural gesture-based retrieval, and inclusive design beyond visual channels.
6. Future Work
Wireless ESP32 integration for untethered wearability.
Miniaturized ring-form factor sensors.
Richer haptic modalities (directional, thermal, ultrasonic).
Adaptive ML-based thresholds and personalization.
Integration with assistive navigation and spatial learning applications.
7. Ethics & Accessibility
Haptic intensity capped to safe tactile levels.
No personal data stored; only numeric pose vectors.
Supports private, silent recall — valuable for visually impaired users.
8. References
Varela, F. J., Thompson, E., & Rosch, E. (1991). The embodied mind. MIT Press.
Clark, A. (1997). Being There. MIT Press.
O’Keefe, J., & Nadel, L. (1978). The hippocampus as a cognitive map. OUP.
Lederman, S. J., & Klatzky, R. L. (1987, 2009). Haptic perception.
Dourish, P. (2001). Where the Action Is. MIT Press.
Brock, A. M. et al. (2015). Human–Computer Interaction, 30(2).
Yates, F. A. (1966). The Art of Memory.
Legge, E. L. et al. (2012). Acta Psychologica.
Pearce, J. M. (2012). Science.
Nosek, B. A. et al. (2015). Science.
9. Citation
Project page: https://www.c11visualarts.com/altered-perception---tactile-memory-recall
GitHub repository: https://github.com/CJD-11/Tacticle-Memory-Recal