Home-Based Monitor for Gait and Activity Analysis

Summary

This innovative device uses magneto-inertial sensors to permit gait and activity analysis in uncontrolled environments. Currently in the qualification process as an outcome measure in the European Medical Agency, one of the applications will be to serve as a clinical endpoint in clinical trials in neuromuscular diseases.

Abstract

Current outcomes in neuromuscular disorder clinical trials include motor function scales, timed tests, and strength measures performed by trained clinical evaluators. These measures are slightly subjective and are performed during a visit to a clinic or hospital and constitute therefore a point assessment. Point assessments can be influenced by daily patient condition or factors such as fatigue, motivation, and intercurrent illness. To enable home-based monitoring of gait and activity, a wearable magneto-inertial sensor (WMIS) has been developed. This device is a movement monitor composed of two very light watch-like sensors and a docking station. Each sensor contains a tri-axial accelerometer, gyroscope, magnetometer, and a barometer that record linear acceleration, angular velocity, the magnetic field of the movement in all directions, and barometric altitude, respectively. The sensors can be worn on the wrist, ankle, or wheelchair to record the subject’s movements during the day. The docking station enables data uploading and recharging of sensor batteries during the night. Data are analyzed using proprietary algorithms to compute parameters representative of the type and intensity of the performed movement. This WMIS can record a set of digital biomarkers, including cumulative variables, such as total number of meters walked, and descriptive gait variables, such as the percentage of the most rapid or longest stride that represents the top performance of patient over a predefined period of time.

Introduction

A number of potential therapies are in development for treatment of genetic neuromuscular diseases. These diseases include Duchenne muscular dystrophy (DMD) and spinal muscular atrophy (SMA) type 3. Subjects with these diseases present initially with proximal lower limb weakness that leads to progressive difficulties in ambulation. The final step in translational research is the demonstration of efficacy of a potential treatment or approach in a clinical trial. Specific, quantifiable, objective, and reliable measures are required. The importance of such measures was recently emphasized by the failure of the phase IIb ataluren trial¹ and the phase III Biomarin trial². One of the likely explanations for these failures was the variability and the nonlinear evolution of the primary outcome measure of these trials, the 6-minute walk test³ (6 MWT). Increasing reliability and sensitivity to the change of outcome measures and the understanding of the factors leading to their variation could contribute to decrease the number of trial failures related to the main outcome measures.

One of the limitations of the current outcomes is the subjectivity of the assessment. To further increase the objectivity of assessments, Heberer et al.⁴ showed that through a marker set and the use of a gait analysis software, there was a significant increase in stride length in patients treated with steroids compared with the naïve group. Hip joint kinetics are early markers of proximal weakness in patients with DMD and are responsive to change with steroid intervention, which is the only available treatment for these patients. Gait laboratories are, however, only available in large clinics. Furthermore, laboratory evaluations are point assessments, and a patient’s condition may greatly vary on a day to day basis due to factors such as fatigue, motivation, and intercurrent illness.

The use of continuous and home-based measurement should achieve both a more objective and a more globally representative assessment. In other fields of neurology, for instance Parkinson⁵ or multiple sclerosis⁶, several studies have assessed the feasibility, reliability, and consistency with other measures of different sensors including accelerometers with or without gyrometers or magnetometers, yet none of these devices is currently a gold standard for evaluation of patients during clinical trials. In the field of neuromuscular diseases, there is currently no validated method for continuous home monitoring of patients. In recent years, through a close collaboration between clinicians and engineers, the Institute of Myology in Paris has developed several devices for upper limb assessment to precisely evaluate upper limb strength and function^7,8,9. A wearable magneto-inertial sensor (WMIS; i.e., ActiMyo) has been developed in collaboration with a company specialized in navigation systems. Initially a monitoring device dedicated to non-ambulant subjects with neuromuscular disorders such as DMD and SMA^10,11, the same device has now been used to monitor ambulant patients in two different configurations: sensors on both ankles or one sensor at the wrist and the other one at the ankle. The configuration for a non-ambulant population is composed of a sensor at the wheelchair and the other one at the wrist.

This WMIS is able to precisely capture and quantify all movements of the limb on which it is placed. The measuring principle is based on the use of microelectromechanical system (MEMS) inertial sensors and magnetometers operated through magneto-inertial equations. Dedicated algorithms allow precise qualification and quantification of patients’ movements in a non-controlled environment. 

The overall goal of the method is to provide identification and quantification of any movement produced by a patient over a pre-defined period of time, and to integrate these measures into disease-specific outcome measures representative of the patient’s condition over a period of time.

To effectively assess ambulant and non-ambulant patients with movement disorders at home, the device must be provided to the patient by a trained evaluator who is responsible for making sure that the instructions have been understood. An investigator and a patient manual are provided with the device. This WMIS is currently being used as an exploratory outcome measure in a number of clinical trials for neuromuscular and neurologic diseases (NCT03351270, NCT02780492, NCT01385917, NCT03039686, NCT03368742, NCT02500381). Specific procedures adapted to the pathology and/or to the clinical trial design have been developed.

Protocol

Any use of the device must be carried out in accordance with the rules established by the reference protocol, validated by the ethics committee and the national regulatory agencies of the country. The use of the device and the various elements attached to it must be done within the intended use described in the patient's manual.

NOTE: To be eligible to use of the WMIS, patient must be over 5 years old, be able to understand and follow the usage rules, provide informed consent, be affiliate or beneficiary of a social security scheme, and be able to comply with all protocol requirements. There are no specific exclusion criteria.

1. Preparing for the participant’s visit at the clinical center

1. Check the suitcase contents: (1) the docking station to plug the sensors during the night for data uploading onto a USB key and recharging of batteries, (2) the power cord divided into two pieces to connect the docking station to a power supply, (3) the Ethernet cable to permit interface with a router, (4) the two sensors to permit daily activity recording, (5) bands for attachment of the sensors depending on the chosen configuration and ambulatory status of the participant (ankle-ankle: two ankle armbands with two stickers to distinguish the wearing side; ankle-wrist: one ankle armband and one bracelet; wrist-wheelchair: one bracelet and one wheelchair pocket), (6) one participant manual and one investigator manual, (7) one task reminder, (8) a screwdriver to enable replacement of the USB key, and (9) two blank USB keys.
   NOTE: If an internet connection is available data transfer occurs automatically
2. Print and prepare the assignment form to record the assignment of a device to a participant. This will enable data reconciliation with the subject ID.

2. Training of the subject during the first visit

1. Positioning of this WMIS
   1. Based on the data that the researchers are seeking as well as the patient’s ambulatory status, use different configurations for the placement of the sensors.
      1. For ambulant patients, fix the two sensors either on a wrist and an ankle for upper and lower limb activity recording or on both ankles for only lower limbs activity.
      2. For non-ambulant patients, fix one sensor on the wrist and the other one on the wheelchair.
2. Explain positioning of the sensors to the participant.
   1. For ambulant participants, fix the two sensors either on a wrist and an ankle or on both ankles.
      1. For the wrist-ankle configuration, place one sensor on the wrist of the dominant hand using the provided bracelet so that the waves are pointing toward the fingers. Place the second sensor on the ankle, on the same side as the wrist sensor, above the external malleolus with the waves pointing in the forward direction.
         NOTE: The sensor must be placed on top of the wrist.
      2. For the ankle-ankle configuration, place a sensor on each ankle, above the external malleolus with the waves pointing in the forward direction.
         NOTE: Stickers should be placed on the sensors to indicate the wearing side.
   2. For non-ambulant participants, fix one sensor on the wrist and the other one on the wheelchair.
      1. For the wrist-wheelchair configuration, place one sensor on the wrist of the participant’s dominant hand using the provided bracelet so that the waves are pointing toward the fingers. Place the second sensor in the bag provided. Attach it on a safe place to the wheelchair.
         NOTE: Independently of the used configuration, do not switch sensors around. The sensors should fit snuggly, but not too tightly to the wrist and/or ankle to prevent them from spinning around.
3. Explain daily routine for sensors’ use to the participant.
   1. Evening routine
      1. Plug the docking station into the power supply. Attach the docking station to the router if an internet connection is available. Insert the sensors into the docking station.
      2. Localize the two light-emitting diodes (LEDs) on the docking station which indicate the status of the sensors. Once plugged into a power source, be sure the station beeps and the diodes become orange to indicate that the sensor batteries are charging, and that data is being downloaded from the sensors to the USB drive.
         NOTE: If the LEDS are still blinking after 5 min, restart the procedure from beginning. If the issue persists, contact the clinical site team.
   2. Morning routine
      1. Verify that the LEDs are green, indicating that the sensors batteries are fully charged, and that data has been cleared from the sensors’ memory. Remove the sensors from the docking station. Wear the sensors in the configuration demonstrated by the evaluator.
         NOTE: If LED on one or both sensors is orange after two consecutive days, contact the clinical center.
   3. Daytime routine
      1. Wear the sensors the entire day and place the sensors back on the docking station at the end of the day.
         NOTE: Remove the sensors during activities involving water, special medical examinations (e.g., magnetic resonance imaging [MRI], CT-scan, X-ray) or any activity that could damage them, and keep them in a safe place on a firm surface. Resume wearing the sensors after the activity.
   4. At the end of the recording period, tidy up all the device items in the suitcase and bring back the device to the clinical center.
      NOTE: Encourage the participant to engage in normal daily activities wearing as much as possible the sensors.
4. Complete a dedicated assignment form.

3. Data collection and analysis

1. Data collection
   NOTE: The sensors record signals continuously for up to 16 h and store the information in an internal memory (Movie 1). The docking station enables the downloading of data stored in the sensors at the end of each day and charging of the batteries during the night. Data downloaded to the docking station is stored on a USB drive that can only be accessed by the evaluators.
   1. A standard 64 GB USB drive can hold up to 3 months of daily recording information (approximately 16 h/day). Provide higher or lower capacity USB drives to adjust as closely as possible to the constraints of the protocols.
   2. If the docking station is not connected to internet, have the evaluator remove the USB drive from the docking station (with the specific screwdriver contained in the suitcase) and replace it with a blank one at the end of the recording period. The USB drive should be sent to the support team for analysis.
      NOTE: If the docking station is connected to the internet, data are uploaded to cloud storage. Thus, there is no need to change the USB drive, as all data are automatically deleted from the USB drive once the files are uploaded into the cloud.
2. Data analysis
   1. At selected time points during the study, extract data from the cloud storage and analyze data using a dedicated algorithm. Adjust the analysis periods and the monitoring reports based on the clinical study.

Results

Data presented here were acquired during clinical trials approved by the ethics committee and the French Regulatory Agency. All patient representatives signed an informed consent.

This WMIS was first used in a clinical study setting in 2012 for controlled and home-based monitoring of upper-limb movements in non-ambulant DMD patients (NCT01611597), which demonstrated the autonomy and feasibility of device use^10<...

Discussion

In the past decade, a number of different systems have been developed, such as an activity monitor (Table of Materials [IV]), which uses accelerometric sensors to monitor activities of daily life for energy expenditure quantification¹³. A triaxial accelerometer (Table of Materials [V]) was used by Tanaka et al.¹⁴ to monitor activity of preschool children. Lau et al.¹⁵ showed through the combination of a dual-accelero...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
ActiMyo Sensors	Sysnav	SF-000080	Wearable magneto-inertal sensors attached to the patient for movment recording
Helen Hayes marker set	Vicon	NA	Whole body jumpsuit with predefined Vicon's spots
OrthoTrak (Motion Analysis, Santa Rosa, CA, USA)	Motion Lab Systems		Gait analysis software
ActiGraph	ActiGraph Corp	GTM1	Activity monitor, used by researchers to capture and record continuous, high resolution physical activity and sleep/wake information
ActivTracer GMS LTD	GMS Co. Ltd Japan	AC-301A	Triaxial accelerometer
ADXL202E dual-accelerometer	Analog Devices	ADXL212AEZ	High precision, low power, complete dual axis accelerometer with signal conditioned, duty cycle modulated outputs, all on a single monolithic IC.
ENC-03J gyroscope	Murata Electronics	ENC-03J	Vibration Sensors
DynaPort MiniMod	MCROBERTS		Small and light case containing a tri-axial accelerometer, a rechargeable battery, an USB connection, and raw data storage on a MicroSD card
MM-2860 Sunhayato	Sunhayato	MM-2860	3-axis accelerometer
MicroStone MA3-10Ac	MA3-04AC	Microstone Co.	Acceleration sensors
RT3 Activity monitor	Abledata	NA	Triaxial accelerometer
Aparito	aparito	NA	Wearables and disease specific mobile apps to deliver patient monitoring outside of the hospital; Elin Davies, Aparito: https://www.aparito.com/
Docking station	Sysnav	SF-000118
Sensor	Sysnav	SF-000080
Bracelet (black/grey L) (black/grey S) (black/yellow L) (black/yellow S)	Sysnav	ZZ-000093 ZZ-000094 ZZ-000247 ZZ-000248
Patient manual	Sysnav	FD-000086
Ethernet cable (2 m max.)	Sysnav	IC-000458
Power cable (EU) (UK) (US)	Sysnav	ZE-000440 ZE-000441 ZE-000442
Power supply unit	Sysnav	ZE-000443
Ankle strap	Sysnav	ZZ-000462
Small bag	Sysnav	ZZ-000033