# Development of a Standardized, Reliable and Easy-to-Use Clinical Instrument to Measure First Ray Mobility and Position of the Medial Forefoot to Assist with Clinical Decisions and Treatments

> **NIH NIH R43** · BIOMED CONSULTING, INC. · 2022 · $259,613

## Abstract

Osteoarthritis (OA) research, a primary component of the NIAMS mission, has focused on the hip, knee, and
hand, with sparse attention to the foot. First metatarsophalangeal (MTP) joint OA (Hallux Rigidus), a source of
substantial pain and limited mobility, is the most common degenerative disease in the foot. Excessive or
insufficient 1st ray mobility (FRM) has been associated with numerous painful, disabling, and limb threatening
pathologies including: tarsometatarsal OA, Hallux Valgus (HV), Hallux Rigidus (HR), metatarsalgia, diabetic
foot ulceration, pes cavus, and pes planus. First ray (medial cuneiform, 1st metatarsal, proximal phalanx, and
hallux) mobility is the superior or inferior displacement of these bony structures in response to a vertically
applied load. While a couple of laboratory devices exist to test 1st ray hypermobility (FRM ≥8mm), there are no
commercially available, reliable, user friendly, FRM devices for the clinic. The study goal is to redesign and
improve the 1st Ray Mobility and Position (MAP1st) version 1 (V1) prototype (PCT/US21/22791) to provide a
clinically viable instrument to measure 1st ray mobility and position. MAP1st V1 has several limitations, including
i) weight, ii) ungrounded hindfoot, iii) visual measurement, iv) tethered laptop, and v) manual data entry. The
Specific Aim is to develop MAP1st version 2 (V2) to increase the reliability, utility, efficiency, and ease
of use for measuring FRM, position, and stiffness. In MAP1st V2, a transducer will measure mobility and
position while a smartphone-based App will replace the laptop and compute stiffness. Outcomes will be stored
in an encrypted file and transferred to electronic medical records. Using this device, and guided by power
analysis, a data set (n=80 feet) will be acquired from 20 healthy individuals with asymptomatic rectus (nrf = 20)
and planus (npf = 20) feet, 10 patients with hallux valgus feet (nhvf = 20) and 10 patients with hallux rigidus feet
(nhrf = 20). Intra-rater and inter-rater reliability will be assessed from replicated measures, while subgroup
differences will also be examined. Device utility will be assessed by distinguishing FRM between the healthy
and pathologic groups using Generalized Estimation Equations (GEE). A usability questionnaire will assess
clinician (MD, DPM, DPT, technician) ease of use for V1 versus V2. Three hypotheses will be tested: (1) Intra-
rater and inter-rater reliability will exhibit an ICC (2,1)>0.75 for use of MAP1st V2; (2) First ray mobility, position,
and stiffness will be different across individuals with asymptomatic rectus, asymptomatic planus, hallux valgus,
and hallux rigidus feet demonstrating device utility; (3) Usability and efficiency will be improved between
MAP1st V1 and V2. This investigational team has collaborated on 10+ projects and co-published 50+
publications on foot biomechanics. Further, pilot data supports MAP1st ability to detect hypermobility in planus
vs. rectus feet. Hence, a smoo...

## Key facts

- **NIH application ID:** 10483379
- **Project number:** 1R43AR080486-01A1
- **Recipient organization:** BIOMED CONSULTING, INC.
- **Principal Investigator:** Howard J. Hillstrom
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $259,613
- **Award type:** 1
- **Project period:** 2022-09-16 → 2025-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10483379

## Citation

> US National Institutes of Health, RePORTER application 10483379, Development of a Standardized, Reliable and Easy-to-Use Clinical Instrument to Measure First Ray Mobility and Position of the Medial Forefoot to Assist with Clinical Decisions and Treatments (1R43AR080486-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10483379. Licensed CC0.

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