The present inventions, in one aspect, are directed to a portable activity monitoring device comprising a housing having a physical size and shape that is adapted to couple to the user's body, a plurality of sensors (for example, motion sensor and altitude sensor) disposed in the housing. The monitoring device may further include processing circuitry, disposed in the housing and electrically coupled to the plurality of sensor, to calculate the activity points corresponding to the physical activity of the user using the sensor data, wherein the activity points correlate to an amount and intensity of the physical activity of the user, and output the data which is representative of the activity points. The monitoring device may also include a display, coupled to the processing circuitry, may output the data which is representative of the activity points to the user.

Portable monitoring devices and methods of operating same

This paper reviews technical and clinical impact of the Microsoft Kinect in physical therapy and rehabilitation. It covers the studies on patients with neurological disorders including stroke, Parkinson’s, cerebral palsy, and MS as well as the elderly patients. Search results in Pubmed and Google scholar reveal increasing interest in using Kinect in medical application. Relevant papers are reviewed and divided into three groups: (1) papers which evaluated Kinect’s accuracy and reliability, (2) papers which used Kinect for a rehabilitation system and provided clinical evaluation involving patients, and (3) papers which proposed a Kinect-based system for rehabilitation but fell short of providing clinical validation. At last, to serve as technical comparison to help future rehabilitation design other sensors similar to Kinect are reviewed.

/pdf/a-review-on-technical-and-clinical-impact-of-microsoft-1cugbrgvga.pdf

A Review on Technical and Clinical Impact of Microsoft Kinect on Physical Therapy and Rehabilitation

This paper reports the results of a "cost-of-illness" study of low back pain (LBP) in Australian adults. It estimates the direct cost of LBP in 2001 to be AU$1.02 billion. Approximately 71% of this amount is for treatment by chiropractors, general practitioners, massage therapists, physiotherapists and acupuncturists. However, the direct costs are minor compared to the indirect costs of AU$8.15 billion giving a total cost of AU$9.17 billion. LBP in Australian adults represents a massive health problem with a significant economic burden. This burden is so great that it has compelling and urgent ramifications for health policy, planning and research. This study identifies that research should concentrate on both direct but particularly the indirect costs including cost-effective management regimes that encourage an early return to duties.

Low back pain in Australian adults: The economic burden

The development of interactive rehabilitation technologies which rely on wearable-sensing for upper body rehabilitation is attracting increasing research interest. This paper reviews related research with the aim: 1) To inventory and classify interactive wearable systems for movement and posture monitoring during upper body rehabilitation, regarding the sensing technology, system measurements and feedback conditions; 2) To gauge the wearability of the wearable systems; 3) To inventory the availability of clinical evidence supporting the effectiveness of related technologies. A systematic literature search was conducted in the following search engines: PubMed, ACM, Scopus and IEEE (January 2010–April 2016). Forty-five papers were included and discussed in a new cuboid taxonomy which consists of 3 dimensions: sensing technology, feedback modalities and system measurements. Wearable sensor systems were developed for persons in: 1) Neuro-rehabilitation: stroke (n = 21), spinal cord injury (n = 1), cerebral palsy (n = 2), Alzheimer (n = 1); 2) Musculoskeletal impairment: ligament rehabilitation (n = 1), arthritis (n = 1), frozen shoulder (n = 1), bones trauma (n = 1); 3) Others: chronic pulmonary obstructive disease (n = 1), chronic pain rehabilitation (n = 1) and other general rehabilitation (n = 14). Accelerometers and inertial measurement units (IMU) are the most frequently used technologies (84% of the papers). They are mostly used in multiple sensor configurations to measure upper limb kinematics and/or trunk posture. Sensors are placed mostly on the trunk, upper arm, the forearm, the wrist, and the finger. Typically sensors are attachable rather than embedded in wearable devices and garments; although studies that embed and integrate sensors are increasing in the last 4 years. 16 studies applied knowledge of result (KR) feedback, 14 studies applied knowledge of performance (KP) feedback and 15 studies applied both in various modalities. 16 studies have conducted their evaluation with patients and reported usability tests, while only three of them conducted clinical trials including one randomized clinical trial. This review has shown that wearable systems are used mostly for the monitoring and provision of feedback on posture and upper extremity movements in stroke rehabilitation. The results indicated that accelerometers and IMUs are the most frequently used sensors, in most cases attached to the body through ad hoc contraptions for the purpose of improving range of motion and movement performance during upper body rehabilitation. Systems featuring sensors embedded in wearable appliances or garments are only beginning to emerge. Similarly, clinical evaluations are scarce and are further needed to provide evidence on effectiveness and pave the path towards implementation in clinical settings.

/pdf/interactive-wearable-systems-for-upper-body-rehabilitation-a-43z4n1945l.pdf

Interactive wearable systems for upper body rehabilitation: a systematic review.

Robots in machining

This paper presents a new sensing system for home-based rehabilitation based on optical linear encoder (OLE), in which the motion of an optical encoder on a code strip is converted to the limb joints' goniometric data. A body sensing module was designed, integrating the OLE and an accelerometer. A sensor network of three sensing modules was established via controller area network bus to capture human arm motion. Experiments were carried out to compare the performance of the OLE module with that of commercial motion capture systems such as electrogoniometers and fiber-optic sensors. The results show that the inexpensive and simple-design OLE's performance is comparable to that of expensive systems. Moreover, a statistical study was conducted to confirm the repeatability and reliability of the sensing system. The OLE-based system has strong potential as an inexpensive tool for motion capture and arm-function evaluation for short-term as well as long-term home-based monitoring.

A Wearable Sensing System for Tracking and Monitoring of Functional Arm Movement

Although numerous researches on s-curve motion profiles have been carried out, up to date, no systematic investigation on the general model of polynomial s-curve motion profiles is considered. In this paper, the model of polynomial s-curve motion profiles is generalized in a recursive form. Based on that, a general algorithm to design s-curve trajectory with time-optimal consideration is proposed. In addition, a special strategy for planning s-curve motion profiles using a trigonometric model is also presented. The algorithms are implemented on a linear motor system. Experimental results show the effectiveness and promising application ability of the algorithms in s-curve motion profiling.

https://journals.sagepub.com/doi/pdf/10.5772/5652

On Algorithms for Planning S-Curve Motion Profiles:

intehweb.com On Algorithms for Planning S-curve Motion Profiles

Although numerous researches on s-curve motion profiles have been carried out, up to date, no systematic investigation on the general model of polynomial s-curve motion profiles is considered. In this paper, the model of polynomial s-curve motion profiles is generalized in a recursive form. Based on that, a general algorithm to design s-curve trajectory with jerk bounded and time-optimal consideration is proposed. In addition, a special strategy for planning s-curve motion profiles using a trigonometric model is also presented. The algorithms are implemented on a linear motor system. Experimental results show the effectiveness and promising application ability of the algorithms in s-curve motion profiling.

Kim Doang Nguyen

Papers

A Wearable Sensing System for Tracking and Monitoring of Functional Arm Movement

On Algorithms for Planning S-Curve Motion Profiles:

intehweb.com On Algorithms for Planning S-curve Motion Profiles

Planning algorithms for s-curve trajectories

Adaptive control of underactuated robots with unmodeled dynamics