care & love
When a patient begins using a gait-assist device — whether a lower limb exoskeleton robot, a powered orthosis, or a simple walking aid — clinicians need reliable ways to measure whether the device is actually helping. While walking speed and step counts are easy to track, the patient's own perspective is equally important. This is where patient-reported outcome measures, or PROMs, come into play.
Patient-reported outcome measures (PROMs) are standardized questionnaires that capture a patient's own assessment of their health, symptoms, functional ability, and quality of life — without interpretation by a clinician. Unlike a timed walking test conducted in a clinic, PROMs reflect how the patient feels in their daily life: whether they can walk to the grocery store, how much pain they experience, and whether they feel confident moving around their home.
PROMs are particularly valuable in gait rehabilitation because they capture dimensions that clinical tests miss. A patient might walk faster on a treadmill after robot-assisted gait training, but if they still feel unstable or fearful of falling at home, the intervention has not fully succeeded.
Gait-assist devices range from simple canes to sophisticated powered exoskeletons. Evaluating their effectiveness requires looking beyond mechanical metrics like torque output or step count. The real question is: does the device improve the patient's life from their own perspective?
PROMs help answer several critical questions:
Researchers and clinicians studying gait training robots and exoskeletons commonly use the following PROMs. Each captures a different dimension of the patient experience.
| PROM Instrument | What It Measures | Typical Use in Gait Studies |
|---|---|---|
| Walking Index for Spinal Cord Injury (WISCI II) | Walking ability with or without devices and assistance, specific to spinal cord injury | Evaluated before and after exoskeleton training programs; widely used in clinical gait rehabilitation trials |
| Patient-Specific Functional Scale (PSFS) | Individualized functional goals identified by the patient (e.g., "walk to the mailbox") | Administered before and after gait-assist device fitting; captures personally meaningful improvements |
| Activities-Specific Balance Confidence (ABC) Scale | Self-reported confidence in performing 16 daily activities without losing balance | Used to assess whether gait-assist devices reduce fear of falling during community ambulation |
| PROMIS Physical Function & Pain Interference | NIH-developed measures of physical function and how pain interferes with daily life | Increasingly used in exoskeleton registries to track long-term outcomes at 6 and 12 months |
| Psychosocial Impact of Assistive Devices Scale (PIADS) | Perceived impact of an assistive device on competence, adaptability, and self-esteem | Specific to device evaluation; captures whether users feel empowered or stigmatized |
| Rate of Perceived Exertion (RPE) / Borg Scale | Self-reported exertion during physical activity | Used session-by-session to ensure training intensity is appropriate and not excessive |
It is important to understand that PROMs and performance-based measures serve different purposes, and the best evaluation protocols use both. Performance-based measures — such as the 10-Meter Walk Test (10MWT), 6-Minute Walk Test (6MWT), and Timed Up and Go (TUG) — provide objective data about what a patient can do under controlled conditions. PROMs, by contrast, reveal what the patient actually experiences in daily life.
A patient may improve their 10MWT speed after training with a lower limb exoskeleton robot, but if their ABC Scale score remains low, they may still avoid walking outdoors. Together, these two types of measures give a complete picture of device effectiveness.
Powered exoskeletons, such as those used in rehabilitation hospitals and increasingly for personal use, are among the most transformative gait-assist devices. PROMs used in exoskeleton trials typically include the WISCI II for spinal cord injury populations, the PSFS for goal-oriented assessment, and the PIADS for psychosocial impact. Studies have shown that exoskeleton users frequently report improvements in bowel and bladder function, spasticity reduction, and sleep quality — outcomes that go well beyond walking speed.
Devices like microprocessor-controlled knee-ankle-foot orthoses have been evaluated using the PSFS, PROMIS Pain Interference, and quality-of-life measures. One-year follow-up data from prospective registries show that patients report significant improvements in functional walking scores and reductions in pain interference, alongside objective gains in walking speed.
In clinical rehabilitation, treadmill-based and overground gait training robots are evaluated with both performance measures (FAC, BBS, TUG, 10MWT, 6MWT) and PROMs. The combination allows clinicians to track functional gains while also capturing the patient's subjective experience of recovery, fatigue, and motivation.
Choosing appropriate PROMs depends on several factors:
As gait-assist devices become more intelligent and personalized, the role of PROMs is evolving. Modern exoskeletons equipped with multi-sensor fusion can identify movement intentions and provide personalized training parameters. When combined with PROM data, clinicians can build a truly individualized rehabilitation plan — one that is driven by both objective sensor data and the patient's own goals and perceptions.
Wearable sensors are also beginning to complement traditional PROMs. By tracking daily step counts, gait symmetry, and activity patterns in the home environment, sensor data can validate or challenge what patients report in questionnaires. This triangulation of objective sensor data, performance-based clinical tests, and patient-reported outcomes represents the gold standard for evaluating gait-assist device effectiveness.
Patient-reported outcome measures are essential tools for understanding whether a gait-assist device truly improves a person's life. By combining PROMs with objective performance tests and emerging sensor technologies, clinicians and researchers can build a complete picture of device effectiveness — one that respects both the measurable data and the lived experience of the patient.