MHealth and thought control.

First came the joystick. Then came the motion-sensing Wii remote. What´s next? Sensors and mobiles are opening up a new world: thought control.

Co-founded by Allan Snyder, a neuroscientist and former University of Cambridge research fellow, Emotiv says its EPOC headset features 16 sensors that push against the player’s scalp to measure electrical activity in the brain – a process known as electro-encephalography. In theory, this allows the player to spin, push, pull, and lift objects on a computer monitor, simply by thinking. “There will be a convergence of gesture-based technology and the brain as a new interface – the Holy Grail is the mind” says Snyder.

Last month the Defence Advanced Research Projects Agency (Darpa), an arm of the US Defence Department, said it had awarded a $6.7 million contract to Northrop Grumman to develop “brainwave binoculars”. The binoculars use scalp-mounted sensors to detect objects the user might have seen but not noticed – in other words, the computer is used as a kind of brain-aid, giving the user superhuman vision.

Explaining the technology, Dr Robert Shin, an assistant professor of neurology and ophthalmology at the University of Maryland School of Medicine, said: “There is a level where the brain can identify things before it ever makes it to the conscious level. Your brain says, ‘it may be something’, but it might not realize that it is something that should rise to the conscious level.”

Another defence contractor, Honeywell, has been working on a similar technology known as “augmented cognition” to help intelligence analysts to operate more effectively. Based on the same principle as the binoculars, it has been shown to make analysts work up to seven times faster. It can also detect when they are getting tired. In other tests, soldiers have been kitted out with headsets that detect “brain overload”, allowing commanders to know if they can process new information under the extreme pressures of the battlefield.

mHealth and Motion capturing.

Motion capture, or Mocap, is a technique for digitally recording movement. Are we playing games her? Originally used as an analysis tool for biomechanics, mocap is now successfully employed in a wide variety of sectors including mHealth related applications.

Movement is captured through the placement of sensors (or markers) on or near each joint of the body. As each joint moves the positions or angles between the markers are recorded. Software records the, angles, velocities, accelerations and impulses, providing an accurate digital representation of the movement.

Realtime data from mocap enables the diagnosis of problems or enhancement of performance in the arenas of biomechanics and sports. It can also assist in the design of products or buildings when applied to the field of engineering or ergonomics. Animazoo distinguishes three types of Mocap´s.

Gyroscopic systems use tiny inertial gyroscopes that are attached to a body. These directly record the rotations of the body parts. The rotational data is transmitted by radio to a receiver unit where it is mapped instantly to a skeleton in order that the data can be visualized in realtime. These systems perform with no lag in realtime, producing incredibly accurate data. The data retains nuance even with fast moves.

Mechanical systems track body joint angles directly and are often referred to as exo-skeleton mocap systems, due to the way the sensors are attached to the body. A person attaches the skeletal-like structure to their body and as they move so do the articulated mechanical parts, measuring the performer’s relative motion. Mechanical motion capture systems are realtime, relatively low-cost and usually wireless. Movement is captured through the placement of sensors (or markers) on or near each joint of the body. As each joint moves the positions or angles between the markers are recorded. Software records the, angles, velocities, accelerations and impulses, providing an accurate digital representation of the movement.

Optical systems triangulate the 3D position of a marker between one, two or more cameras that have been pre-calibrated for distance to provide overlapping projections. Tracking a large number of markers or multiple performers is accomplished by the adding more cameras. These systems can be expensive to buy, require technical expertise to operate and are studio based. They have a relatively small capture area and can suffer from occlusion as well as being complicated to set up. Magnetic and electrical interference makes these systems highly susceptible to error, they also require extensive data cleaning and technical expertise to operate plus they suffer from limited area of use and lag for realtime use.

Magnetic systems calculate position and orientation by measuring the relative magnetic flux of three orthogonal coils on both the transmitter and each receiver. Magnetic systems require only two-thirds the number of markers compared to optical systems. One drawback is that the markers are susceptible to magnetic and electrical interference from metal objects in the environment and electrical sources. Magnetic and electrical interference makes these systems highly susceptible to error, they also require extensive data cleaning and technical expertise to operate plus they suffer from limited area of use and lag for realtime use.

Basic components for building mHealth devices.

One step beyond the platform is adding other components. What do you create when your motto is “Computing stuff tied to the physical world?”  A tiny, fairly well featured kit with wireless capability. The JeeNode wireless communication platform.

It looks like a fun and cost effective way to get into experimenting with RF communication. By combining an Arduino-compatible processor (ATmega328) with a low-cost HopeRF radio module, Jean-Claude Wippler in a town called Houten, The Netherlands,  creates these building blocks and offering them for sale as a kit, or, since it is an open source hardware design, you can just download the PCB layout and roll your own. You can think of lots of applications (remote candle lighter, interactive cat toy:)) that aren’t worth a full xBee-based solution, where it would be handy to have a development board like this that I could just drop in and use.

Jee Labs also has a weblog with daily news about projects being worked on in the fascinating world of physical computing, wireless comm’s, sensors, lights, switches, motors, robots, WSN’s, Arduino’s, you name it.

Building a sensornetwork for mHealth purposes.

For a wireless sensor network you need a platform to start with. But what? Arduino is an open-source electronics prototyping platform based on flexible, easy-to-use hardware and software. It’s intended for artists, designers, hobbyists, and anyone interested in creating interactive objects or environments.

Arduino can sense the environment by receiving input from a variety of sensors and can affect its surroundings by controlling lights, motors, and other actuators. The microcontroller on the board is programmed using the Arduino programming language (based on Wiring) and the Arduino development environment (based on Processing). Arduino projects can be stand-alone or they can communicate with software on running on a computer (e.g. Flash, Processing, MaxMSP).

The boards can be built by hand or purchased preassembled. The software can be downloaded for free. The hardware reference designs (CAD files) are available under an open-source license, you are free to adapt them to your needs.

Wireless Sensor Networks and mHealth basics 3.

Last theory on Wireless Sensor Networks coming up. What about the software, middleware and programming languages?

Software

Energy is the scarcest resource of WSN nodes, and it determines the lifetime of WSNs. WSNs are meant to be deployed in large numbers in various environments, including remote and hostile regions, with ad-hoc communications as key. For this reason, algorithms and protocols need to address the following issues:

• Lifetime maximization
• Robustness and fault tolerance
• Self-configuration

Middleware

There is considerable research effort currently invested in the design of middleware for WSN’s. In general approaches can be classified into distributed database, mobile agents, and event-based.

Programming languages

Programming the sensor nodes is difficult when compared with normal computer systems. The resource constrained nature of these nodes gives rise to new programming models although most nodes are currently programmed in C.

• c@t (Computation at a point in space (@) Time)
• DCL (Distributed Compositional Language)
• galsC
• LabVIEW
• nesC
• Protothreads
• SNACK
• SNAPpy (Python)
• SQTL
• Java Sun SPOT
• uSWN

Wireless Sensor Networks and mHealth basics 2.

What standards, hardware and operating systems are  used for wireless sensor networks? There are three. I wrote some articles about ZigBee. It´s a proprietary mesh-networking specification intended for uses such as embedded sensing, medical data collection and home automation. WirelessHART is specifically designed for Industrial applications. 6LoWPAN is the IETF standards track specification. Also relevant to sensor networks is the emerging IEEE 1451 which attempts to create standards for the smart sensor market. The main point of smart sensors is to move the processing intelligence closer to the sensing device.

Hardware

The main challenge is to produce low cost and tiny sensor nodes. With respect to these objectives, current sensor nodes are mainly prototypes. Miniaturization and low cost are understood to follow from recent and future progress. Some of the existing sensor nodes are given below. Some of the nodes are still in research stage. Also inherent to sensor network adoption is the availability of a very low power method for acquiring sensor data wirelessly.

Operating systems

Operating systems for wireless sensor network nodes are typically less complex than general-purpose operating systems both because of the special requirements of sensor network applications and because of the resource constraints in sensor network hardware platforms. Wireless sensor network hardware is not different from traditional embedded systems and it is therefore possible to use embedded operating systems such as eCos or uC/OS for sensor networks. However, such operating systems are often designed with real-time properties. Unlike traditional embedded operating systems, however, operating systems specifically targeting sensor networks often do not have real-time support.

TinyOS is perhaps the first operating system specifically designed for wireless sensor networks. Unlike most other operating systems, TinyOS is based on an event-driven programming model instead of multithreading. TinyOS programs are composed into event handlers and tasks with run to completion-semantics. When an external event occurs, such as an incoming data packet or a sensor reading, TinyOS calls the appropriate event handler to handle the event. Event handlers can post tasks that are scheduled by the TinyOS kernel some time later. Both the TinyOS system and programs written for TinyOS are written in a special programming language called nesC which is an extension to the C programming language.

There are also operating systems that allow programming in C. Examples of such operating systems include Contiki, MANTIS, BTnut, SOS and Nano-RK. LiteOS is a newly developed OS for wireless sensor networks, which provides UNIX like abstraction and support for C programming language.

Wireless Sensor Networks and mHealth basics 1.

Building a Wireless Sensor Network is fine, but what are the unique characteristics of such a network:

• Limited power they can harvest or store
• Ability to withstand harsh environmental conditions
• Ability to cope with node failures
• Mobility of nodes
• Dynamic network topology
• Communication failures
• Heterogeneity of nodes
• Large scale of deployment
• Unattended operation
• Node capacity is scalable,only limited by bandwidth of gateway node.

Sensor nodes can be imagined as small computers, extremely basic in terms of their interfaces and their components. They usually consist of a processing unit with limited computational power and limited memory, sensors (including specific conditioning circuitry), a communication device (usually radio transceivers or alternatively optical), and a power source usually in the form of a battery. Other possible inclusions are energy harvesting modules, secondary ASICs, and possibly secondary communication devices (e.g. RS-232 or USB).

The base stations are one or more distinguished components of the WSN with much more computational, energy and communication resources. They act as a gateway between sensor nodes and the end user.

Wireless network candidates for mHealth systems.

A recent report by ON World, “WSN for Healthcare” estimates that wireless sensor networks can reduce annual health care costs by US $25 billion by 2012. Much of that savings is derived by reducing hospitalizations and extending independent living for seniors. “They can reduce” but how? In the market for wireless sensor chips are two contenders maximum. More than eight competitors are fighting. What is at stake is the prize of becoming the standard for connecting low power consumer products to the next generation of mobile phones and enabling smart energy devices within the home.

A quick high level intro to some of the technologies:

Wavenis is the ultra low power (ULP), long range capable, wireless technology intended for use for digital data transmission. Based on the Wavenis RF ASIC and the associated protocol stack, the solution integrates point-to-point, broadcast, polling, repeater and also specific mesh network and self-routing algorithms suitable for Ultra Low Power networks operation. In addition, Wavenis has been designed to feature Bluetooth extension capabilities to open the standardization way for such an ULP wireless solution.

Sensium is an ultra low power sensor interface and transceiver platform for a wide range of applications in healthcare and lifestyle management. The device includes a reconfigurable sensor interface, digital block with 8051 processor and an RF transceiver block. On chip program and data memory permits local processing of signals. This capability can significantly reduce the transmit data payload. Together with an appropriate external sensor, the Sensium provides ultra low power monitoring of ECG, temperature, blood glucose and oxygen levels. It can also interface to 3 axis accelerometers, pressure sensors and includes a temperature sensor on chip. One or more Sensium enabled digital plasters continuously monitor key physiological parameters on the body and report to a basestation Sensium plugged into a PDA or Smartphone. The data can be further filtered and processed there by application software.

ZigBee Health Care provides a global standard for interoperable wireless devices enabling secure and reliable monitoring and management of noncritical, low-acuity healthcare services targeted at chronic disease management, obesity and ageing. ZigBee Health Care is designed for use in homes, fitness centers, retirement communities, nursing homes and a variety of medical care facilities. Products using ZigBee Health Care may be wearable, portable or fixed, depending on needs. In addition, ZigBee Health Care products can interact with the broader ecosystem of ZigBee wireless technology devices that may be found in typical home and commercial settings. It also provides full support for IEEE 11073 devices including glucometers, pulse oximeters, electrocardiographs, weight scales, thermometers, blood pressure monitors and respirometers.

ANT is a Wireless Sensor Network (WSN) RF protocol for almost all practical ultra-low power networking applications – from simple point-to-point to complex mesh networks. ANT is designed to run using low cost, low power microcontrollers (MCUs) and transceivers operating in the 2.4 GHz Industrial, Scientific and Medical (ISM) band. The ISM band is a globally available licence-free part of the RF spectrum. The worldwide adoption of the 2.4 GHz band lends itself to cost critical consumer applications such as sports and health products because a single product design can be shipped to a global customer base without modification. The ANT WSN protocol has been intentionally engineered for simplicity and efficiency.

Bluetooth Low Energy technology is a short-range communications technology. The core system consists of an RF transceiver, baseband, and protocol stack. The system offers services that enable the connection of devices and the exchange of a variety of data classes between these devices. It will give devices the possiblity to consume only a fraction of the power of classic Bluetooth enabled products. In many cases, low energy products will operate more than a year on a tiny button cell battery without the need for recharging. By strengthening the technology’s ability to provide wireless connectivity for smaller devices, low energy rounds out the total Bluetooth wireless Personal Area Networking (PAN) offering.

BodyLAN is an ultra low power, reliable and low cost, 2.4 GHz wireless protocol that is easy to implement and specifically designed to handle health, wellness and fitness applications. BodyLAN devices use only a small coin-cell battery that can last for years depending on the application. This enables the deployment of miniature wireless, health, fitness and wellness devices. FitLinxx built this protocol as a direct response to their own critical need to conserve power, keep costs to a minimum, manage and control millions of dispersed devices and make sure end users have a great experience. BodyLAN is offered in multiple configurations including chip sets, modules and access points. BodyLAN has been implemented in millions of devices including consumer fitness products, weight scales, blood pressure monitors, peak flow meters, heart rate monitors, fitness equipment and consumer electronics products.

Z-Wave is the first technology to bring affordable, reliable and easy-to-use wireless control to every aspect of daily life – the home, consumer electronics, healthcare, and energy use, to name just a few. Z-Wave is an award-winning, proven and interoperable* wireless mesh networking technology that allows a wide array of devices in and around the home to communicate including lighting, appliances, HVAC, entertainment centers, and security systems. Z-Wave brings many benefits to everyday life including remote home monitoring, home healthcare, safety and security, and energy conservation. Z-Wave certified products are currently available from leading consumer brands in more than 300 products.