Table 1.
Subject demographics.
Fig 1.
Inertial measurement unit (IMU) placement on MWC.
The image illustrates the placement of the three MWC-mounted IMUs. The IMUs were secured with custom 3D-printed holders. Red circles indicate the mounting locations at both wheel hubs and the wheelchair frame.
Fig 2.
Wheelchair Pivot Maneuver for IMU Synchronization.
Schematic illustration of a wheelchair pivot maneuver. The sequence shows four positions during the maneuver: starting position (left), clockwise rotation (middle-left), counterclockwise rotation (middle-right), and return to starting position (right). Red arrows indicate the direction of rotation. This standardized movement pattern creates distinct angular velocity measurements across all IMUs.
Fig 3.
Data processing for multi-sensor synchronization.
i. Raw sensor data from 3 sensors is separated into daily sections, from 3:00 am of the current day to 2:59 am of the next day, ii. Angular velocity measurements are corrected by removing any systematic offset for each axis, iii. Orientation quaternions were computed using an open-source gradient descent algorithm [26] that fuses accelerometer and gyroscope data to estimate sensor orientation in a computationally efficient manner. iv. Angular velocity is transformed into the inertial frame using the calculated orientation, v. angular velocity is filtered vi. Processed data for each day is saved separately, containing corrected angular velocity, acceleration, world-frame z-axis angular velocity, orientation quaternions, and temperature, vii. All processed sensor data for the day is combined into a single dataset, viii. Synchronization movements are identified using the world-frame angular velocity, viiii. Temporal drift between sensors is determined using cross-correlation and corrected, x. Data is synchronized across sensors, xi. Save data.
Fig 4.
Reference frame definitions for IMU-wheelchair alignment.
Illustration of three coordinate reference frames used for IMU data analysis on a manual wheelchair. (A) A sensor-fixed frame, which is fixed to and rotates with the IMU. (B) A wheelchair-fixed frame is fixed to and rotates with the wheelchair with axes aligned with axes consistent with vehicle dynamics. (C) An inertial frame, which is fixed relative to gravity and an arbitrary heading direction and does not rotate with the sensor or wheelchair.
Table 2.
Mobility metrics definitions and sensors used.
Fig 5.
Movement bouts and bout continuity.
Time series plot showing wheelchair speed data for a single participant, illustrating key bout metrics. The figure highlights three distinct movement bouts.
Fig 6.
Relationship between wheelchair speed and slope during real-world mobility.
Wheelchair speed and pitch angle data (slope) for a single participant over a portion of a day (approximately 5 minutes).
Table 3.
Descriptive statistics for all mobility bouts (n = 6024).
Fig 7.
Comparison of mobility metrics across participants and SCI levels.
(a) Total data analysis periods in hours and number of movement bouts per 7-day collection by participant. (b) Mobility bout movement duration (s), distance (m), and mean speed (m/s) across participants. Participants with red data points have a low-level SCI, blue data points have a mid-level SCI, and green data points have a high-level SCI.
Fig 8.
Distribution of time spent at different wheelchair speeds for each participant over one week.
The bin width in the histogram is 0.1 m/s. Note that only the speeds between 0 and 2 m/s are shown to provide a closer view of the slower-speed range.
Fig 9.
Comparison of the mean mobility bout characteristics for short (blue), medium (orange), and long (yellow) duration bouts for all participants.
Table 4.
Mobility metrics for 7-day collection.
Table 5.
Key daily mobility metric statistics.
Fig 10.
Mean bout slopes across all movement bouts for 12 participants.
The x-axis represents the participants, while the y-axis shows the mean bout slope in degrees, with data ranging from 0 to 11 degrees. The black line at approximately 4.8 degrees represents the ADA (Americans with Disabilities Act) compliant slope angle limit, and the percentage represents the percentage of each participant’s navigated slopes that were steeper than the ADA recommendation.
Fig 11.
7-day mobility metrics across three SCI injury levels: Low (T9-L1), Mid (T1-T8), and High (C6-C8).
Each plot’s scale starts at zero in the center, with the maximum value representing the highest value across all subjects for all short duration movement bouts. Total distance and movement duration represent the cumulative 7-day data for all short movement bouts.
Fig 12.
Comparison of 7 Day Mobility Profiles between Participant 6 (P6) and Participant 12 (P12), across various metrics.
P6 (blue) and P12 (orange), are both 50-59 years old. The metrics show P6 had more turns (10290 vs. 3377), starts/stops (4273 vs. 1426), short duration (<215s) mobility bouts (608 vs. 318), and medium (215-700s) and long duration (>700s) bouts. The short duration bout spider plot also reveals P6 had longer total 7-day movement duration, higher maximum speed, and higher mean speed compared to P12.
Table 6.
Comparison of studies measuring daily MWC use in everyday life.